Text2026
Ricursive Intelligence · USA
A dense (not MoE) model with 65B parameters, pretrained on 12 trillion tokens, with a context of up to 1 million tokens. It is built for programming and agents: by the authors' own test it scores 80.52 on Terminal-Bench 2.1 and beats much larger American open models (Reflection Beam 501B with 80.1, Meta Muse Spark Open 816B with 76.4, NVIDIA Nemotron 3 Ultra 550B with 56.4). The authors started from the Olmo 3 recipe and claim a 16 to 55 times gain in training efficiency on code. It was designed for NVIDIA graphics cards. BF16 and NVFP4 are published for the instruction-tuned version, plus a BF16 base. This is a preview release, and the figures are the authors' own, not independent.
- an agent for programming in the terminal and a repository
- long tasks with a context of hundreds of thousands of tokens
- your own tuning on top of an open base model
- Sizes
- 65B (dense)
- Hardware
- from: Cluster
Image generationRU2022–2026
Sber (Kandinsky Lab) · Russia
Sber's Russian family of image and video generation models. Understands Russian-language prompts and Russian cultural context well; released under MIT. The new Kandinsky S2V 1.0 (Avatar, MIT) animates a person from a single frame to a speech recording: the whole figure moves, with expressions and gestures, in clips of up to a minute. Pro (HD) and Lite (SD, runs on a home graphics card) versions; it was trained on more than a million fragments in 95 languages.
- Images from Russian-language descriptions
- Short promo videos from text or a photo
- Instruction-based image editing
- Sizes
- 2B – 21B
- Hardware
- from: 1 GPU
TextGGUF2024–2026
Sarvam AI · India
Indian models focused on 22 languages of India. Sarvam 30B and 105B (2026) are MoE models with strong reasoning and agent skills. In November Sarvam-Prism came out (Apache 2.0, based on Sarvam-105B): a decision model that, given a context and questions with fixed answer options, returns the probability of each in one pass and writes no text. It needs a graphics card with FP8 and about 120 GB of memory (B200 or H200); a paid API exists too.
- Multilingual customer support
- Reasoning and calculation tasks
- Agents with tool calling
- Sizes
- 2B – 105B-A10B
- Hardware
- from: Laptop
Image + text2026
Microsoft · USA
A compact 4B model that operates a computer by itself: it looks at a screenshot and clicks, and when that is more efficient it switches to the command line and edits files with code. Both roles are in one model, with no external orchestrator. On the OSWorld-Verified test (50 steps) it scores 66.0%, which the authors say is the best result among 4B models, and 87.5% on operating-system tasks. It was trained from the intermediate Mage-VL in five stages, with a set of almost 294 thousand synthetic tasks over 6,915 skills. The context for training and running is 32,768 tokens, and the architecture holds up to 262,144. It suits office automation and assistants on your own computer. The figures come from the authors.
- an agent that works in applications through screenshots and the command line
- automating office tasks on your own computer without a cloud
- a prototype assistant that operates the desktop
- Sizes
- 4B
- Hardware
- from: Laptop
Text2026
Nanbeige · China
A 33B model that the authors call the senior teacher for future lightweight agents: they plan to train small models (for example 3B) on it. It is strong in programming and office tasks: on the JobBench test across 35 professions it beats the baseline in most, according to the authors. Context up to 512 thousand tokens, reasoning can be switched on and off, and tool calling works best in the XML format. The authors compare it with Qwen3.8-27B, Muse-Glimmer-30B and Gemma 4 31B and say it leads on most tests; the figures are their own. A base version is published too.
- an agent for programming and working with tools
- office tasks by profession: reports, tables, document analysis
- a base model for your own fine-tuning
- Sizes
- 33B
- Hardware
- from: 1 GPU
Video2026
Tencent Hunyuan · China
A "living world" video model: it builds the world segment by segment, and you steer it with text and a camera trajectory. At each step you can add an object, change the style or scene, describe an action or turn the camera, and the memory of the world carries over between segments. Output is 720 by 1280 at 24 frames per second, and a segment takes 8 steps. The standard configuration is meant for several graphics cards, but there is a variant for a single RTX 4090 with INT8 weights and part of the model offloaded to the CPU. For narrow areas such as robotics a light LoRA tuning can be attached. Together with the model came the Hy-Nomas-Bench set of 280 test cases; the technical report and tests of the model itself are promised later.
- interactive video worlds and game-scene prototypes from a description
- test videos for robotics with LoRA tuning
- experiments with a controllable camera and scene consistency
- Sizes
- not stated (54 MMDiT blocks, a Qwen2.5-VL-7B text encoder)
- Hardware
- from: 1 GPU
Text2025–2026
Ant Group (inclusionAI) · China
An Ant Group family: Ling for standard models, Ring for reasoning ones. There are trillion-parameter flagships and the efficient Ling-3.0-tiny, which needs only 1.3 billion active parameters. The new Ling-3.1-flash (560B, 25B active, 1M-token context) targets agents, office tasks and development. The improved Ling-3.1-flash-1019 (MIT) raised the Artificial Analysis index from 41 to 44 by the authors estimate.
- Corporate assistant
- Agents for office processes
- Financial analytics (Fin version available)
- Sizes
- 7.9B-A1.3B – 1T
- Hardware
- from: Laptop
Documents and OCROllama2026
OpenBMB (ModelBest) · China
The first MiniCPM model built only for documents: it reads text, tables, formulas, charts and seals, and pulls the needed fields out of papers. Just 1.3B. By the authors' tests, 93.68 on Real5-OmniDocBench (document parsing in real conditions: scans, photos, skewed and recaptured pages) and 54.7 on OCRBench v2. Chinese and English are stated, Russian is not. An auxiliary DSpark model is published for it that speeds up generation: according to the authors processing is 55% faster, and the speed is about 1.5 times that of PaddleOCR-VL-1.6 and 3.6 times that of MinerU2.5 Pro. It runs in vLLM, SGLang, llama.cpp and Ollama, with compressed GGUF, AWQ and GPTQ versions.
- parsing scans and photos of documents into markup: text, tables, formulas
- extracting fields from invoices, contracts and forms in Chinese and English
- fast processing of a document flow on a small server
- Sizes
- 1.3B
- Hardware
- from: Laptop
Text2026
XHToken (the Spark project) · not stated
A compact 4B model to run right on a device, focused on agents: tool calling, multi-step planning, programming, long context. Version 2.6 came about a month after 2.5 with the same architecture and improved only through further training. The reasoning budget is adjustable: none, low, high. The authors state that it holds its own against models of around 9B. Languages on the card: English and Chinese, Russian is not stated. Running it needs the model's own code in transformers. The figures come from the authors. At the end of October a 1.7B size was added (INT4, INT8, FP8).
- an agent with tool calling on a home computer or laptop
- a local programmer assistant that does not need a big server
- AI built into an app with a choice of how much the model thinks
- Sizes
- 1.7B и 4B
- Hardware
- from: Laptop
Documents and OCR2026
Baidu · China
Baidu's OCR model building on DeepSeek-OCR ideas: processes multi-page documents and PDFs in a single pass and outputs structured text. Claimed to be multilingual, but the language list is not published. On October 27 Unlimited-OCR-2 (MIT, about 3.3B) came out: according to the authors it parses documents of unlimited length (the SR-SWA technique), and the MarathonDocBench set for very long documents was published with it.
- Converting multi-page PDFs and scans to text and Markdown
- Recognizing contracts, invoices and reports
- Preparing document archives for search and RAG
- Sizes
- 3.3B
- Hardware
- from: Laptop
Text analysisRU2026
vLLM Semantic Router project · international project
An open family of models for an AI gateway: they answer a request with probabilities without generating text. They detect topic and urgency, jailbreak attempts, harmful requests, personal data and whether a tool is needed. Small versions run on a CPU, Vela understands 17 languages including Russian. The new d3 (27B) also reads several images and videos, and d3-turbo is, by the authors' own estimate, 4 points more accurate on text. The newest in the line, d3-ultra, came out on October 24.
- routing requests between models and teams
- checking a request for a jailbreak attempt or harmful content before the main model
- finding personal data with positions in a text
- Sizes
- 0.3B – 27B
- Hardware
- from: Laptop
Medicine2026
Hugging Face (HuggingFaceBio) · USA
An open 14.8B language model for working with DNA, built on Qwen3-14B. You send a raw sequence right in an ordinary chat, and it answers in English: it judges whether a mutation is benign or pathogenic, finds regions that control gene activity, assigns a sequence to an organism group, predicts the next bases and explains its reasoning. DNA and text go in one stream, with DNA encoded in groups of six bases. By the authors' tests, on five sets it scores 66.7% without reasoning, 27 points above Qwen3-14B, and costs about 1,800 times less than GPT-6.1 Sol at a close result. It fits on a single 80 GB card, so sensitive data can stay with you. Viral data was excluded from training because of the risks. The conclusions are computed and do not replace laboratory verification.
- assessing DNA variants: benign or pathogenic
- finding regions that control gene activity
- a research assistant for biologists on your own server
- Sizes
- 14.8B
- Hardware
- from: 1 GPU
Text to speech2026
inclusionAI (Ant Group) · China
A family of open speech models from Ant Group: a dense 0.5B based on Qwen2.5-0.5B and the MoE version tiny (7.9B parameters, about 1.3B active, based on Ling V3). They clone a voice from a short sample, create a voice from a description in words, and control delivery, emotion, speed, pitch and volume. There are more than 100 built-in Chinese voices, five English ones and 14 inline tags for a breath, cough, laugh, sigh and hesitation. Languages: Chinese, English, German, Spanish, French, Korean, Japanese and the Sichuanese and Cantonese dialects, no Russian. Sample rate is 44.1 kHz. Running it needs the code from the GitHub repository, and the Hugging Face page only distributes the weights. There is a Comfy-Org build for ComfyUI.
- voicing videos and podcasts in Chinese and English with emotion control
- cloning a voice from a short sample
- creating a voice from a description for games and apps
- Sizes
- 0.5B and 7.9B-A1.3B (tiny)
- Hardware
- from: Laptop
3D2026
NVIDIA · USA
A diffusion model that creates three-dimensional body animation from a text description and set conditions: poses, positions of hands and feet, a route and points to pass through. There are versions for the SOMA skeleton (30 joints), the Unitree G1 robot (34 joints) and the SMPL-X human (22 joints). Version 1.2 is trained on a corrected set: in 1.1 some test recordings leaked into training, so the new version is the one to compare against other models. According to the authors, foot skating is reduced and text following is slightly weaker. The data of some variants is proprietary (Bones Rigplay), while the open variants are trained on Bones-SEED.
- animating characters for games and video from a description
- motions for humanoid robots (the Unitree G1 skeleton)
- motion drafts with a given route and poses
- Sizes
- not stated
- Hardware
- from: 1 GPU
Robotics2025–2026
NVIDIA · USA
"World" models for robots and self-driving vehicles: they generate realistic video of physical scenes and predict actions. Cosmos 3 combines understanding, generation and control. In October the surgical versions came out: Cosmos3-H-Embodied-Nano (16B, one model for predicting video, actions and policy on surgical robots) and Cosmos3-H-Dreams (a real-time world for simulating operations with the Versius robot). They are under the NVIDIA Open Model License.
- Synthetic video for training robots and self-driving vehicles
- Testing scenarios in simulation
- Robot control (Policy versions)
- Sizes
- 2B – 65B
- Hardware
- from: 1 GPU
Text2026
KRAFTON AI · South Korea
A model from the Korean KRAFTON (the publisher of PUBG) with 30B parameters, 4B active, trained from scratch. It is strong in Korean conversation and agentic tasks: it can reason and call tools, and works with Hermes Agent, Pi and OpenCode. Training languages: Korean, English, Japanese, Chinese, Spanish, French, Thai, and Russian is not among them. There are compressed MXFP8 and NVFP4 versions and an auxiliary model for faster generation. This is a trial release (preview), and the specifications may change before the final one. The weights are issued on request on Hugging Face, and the benchmark figures are the authors' own.
- a Korean-language assistant and customer support
- an agent with tool calling on your own server
- game and media projects for a Korean audience
- Sizes
- 30B-A4B
- Hardware
- from: 1 GPU
Code2026
Recursive · not stated
An open expert model (39.8B parameters, 2.5B active per token) for coding agents: it digs into someone else's repository, fixes bugs, writes functions and tests, and can reason and call tools over several steps. Trained from scratch, 262 thousand token context, text only. It weighs about 80 GB, and the authors run it on a single B300 or H200 card through SGLang. By the authors' own tests: Terminal-Bench 2.1 54.9%, SWE-bench Pro v2 89.7%, SWE-bench Verified 74.2%. Part of the comparisons come from other developers' own reports, and the test conditions differ between sources.
- an agent for fixing bugs and extending a repository in the terminal
- writing tests and new functions from a description
- a local developer assistant on your own server
- Sizes
- 39.8B-A2.5B
- Hardware
- from: 1 GPU
Text analysis2026
Contrastive-LM (per the announcement: Stanford together with NVIDIA) · USA
An open fast-choice model for agents: it takes a description of a situation and a set of options and returns the probability of each without generating text. It can answer yes or no, pick from a list and give a score on a scale. Actions and state are encoded separately, so action vectors can be computed in advance: by the authors' measurements, with a choice among about a thousand options it is up to 13 times faster than the Jev analogue. After fine-tuning it works as a verifier that picks the best of several solutions of a coding agent (DeepSWE 81.6%, Terminal-Bench 2.1 87.6% by their measurements). It needs Linux, an NVIDIA card and Qwen3-8B in vLLM, and the card language is English.
- fast choice of an agent's next action from given options
- checking and ranking several solutions of a coding agent
- routing requests: department, urgency, a score on a scale
- Sizes
- 8B (a frozen Qwen3-8B plus two small projection heads)
- Hardware
- from: 1 GPU
CodeOllama2026
DeepReinforce · not disclosed
Models for agentic development: they build their own plan and scaffolding for a task and execute it in the terminal. Fine-tuned from Qwen 3.5 and Gemma 4; work with Claude Code, OpenHands and similar tools. In October Ornith-1.5-122B (MoE, MIT) came out: according to the authors it is stronger and faster than the previous ones, writes shorter and is meant for a single DGX-class card; compressed FP8, NVFP4, GGUF and MLX versions exist. The figures come from the authors.
- A developer agent in the terminal
- Fixing bugs from a task description
- Understanding and extending a large repository
- Sizes
- 9B – 397B
- Hardware
- from: 1 GPU
Weather and climate2024–2026
Allen Institute for AI (Ai2) · USA
A fast climate model emulator: simulates the atmosphere years and decades ahead on a single GPU. Coupled with an ocean model (SamudrACE) for long-term scenarios. The new HiRO-ACEv2 adds a diffusion model that sharpens the coarse 100 km grid to 3 km: precipitation, wind and pressure every 6 hours for decades ahead, worldwide or for a chosen region. By the estimate of Ai2, global 3 km data come out about 300 times cheaper than with the X-SHiELD model. For now it reproduces only the X-SHiELD climate, not real weather from the archive.
- Decades-long climate scenarios to assess long-term asset risks
- Large-scale what-if runs on temperature and precipitation
- Preparing data for crop yield and energy demand models
- Sizes
- checkpoint of about 1.8 GB
- Hardware
- from: 1 GPU
Text2026
jialinyyzz (sgaofen) · not stated
A 12B model that rewrites drafts written by AI so that they read like a person wrote them: emails, essays, reports, forum posts. It is trained to keep every number, unit, date, name and quote and to add nothing. It runs on your own computer; there is a ready app for Mac and Windows that works offline, and GGUF files of different compression for llama.cpp. Stated languages: English and Chinese, Russian is not stated. By the author's measurements, the Originality.ai detector judged 95% of the English rewrites human. The result still has to be read through, especially numbers and names.
- rewriting drafts of emails and reports so that they sound more natural
- editing texts after AI without losing numbers, dates and quotes
- local processing of texts that must not be sent to the cloud
- Sizes
- 12B
- Hardware
- from: Laptop
Text analysis2026
Tencent Hunyuan · China
A model that runs the long-term memory of an AI agent: it decides what from a chat, work tasks or code is worth remembering, in what form, and how new information changes what is already stored. It replaces the general-purpose model inside the memory systems Mem0, MemOS and Tencent's own Hy-Memory. Languages on the card: English and Chinese. The benchmark figures are Tencent's own.
- an assistant's memory about a customer between conversations
- remembering the course of work on a project and code
- updating stored facts when new data arrives instead of duplicates
- Sizes
- 30B-A3B
- Hardware
- from: 1 GPU
Image generation2026
OpenMOSS · China
A text-to-image model. It takes an ordinary description, sets of tags and a JSON layout in which you can set where a caption stands and how objects are arranged. It renders text in English and Chinese well. Base and fine-tuned (SFT) versions exist, and it plugs into ComfyUI. It uses a text encoder based on Qwen3.5-9B and the FLUX.2 decoder. The community is already fine-tuning it: Kromoss (lodestones) removes the blurriness of the base version, is a drop-in replacement for SFT and comes with an 8-step speed-up LoRA.
- banners and covers with captions
- infographics and posters with a given layout
- pictures for product cards
- Sizes
- about 5B
- Hardware
- from: 1 GPU
TextOllama2026
ConwayResearch (Underdog) · not stated
Qwen3.8-27B squeezed to 2 bits into a single 7.9 GB GGUF file instead of 54 GB, with the focus on keeping tool calling intact. By the authors' measurements (their Underdog Bench), tool calling is 88 against 84 for the full model, parallel calls 42 against 35, and on average 96% of the full model's quality across nine tests. It runs on plain llama.cpp and Ollama, thinking mode can be switched on and off, and it understands images with a separate vision file (about 0.6 to 0.9 GB). Language stated on the card: English.
- an agent with tool calling on a home graphics card
- a local coding assistant with functions
- analysing pictures with the vision file attached
- Sizes
- 27B (7.9 GB file)
- Hardware
- from: Laptop
Text2026
Reflection AI · USA
An open model from the American company Reflection with 501B parameters (23B active, a 1 million token context), text only, mainly English. Stated as economical in reasoning: according to the authors it needs about three times fewer tokens for thinking at comparable quality. Strong in programming, tool calling and science. Weights in BF16, FP8 and NVFP4. The benchmark figures are the authors' own.
- an agent for solving tasks in a repository and a terminal
- long tasks with tools and search (via MCP)
- solving scientific and mathematical problems with reasoning
- Sizes
- 501B-A23B
- Hardware
- from: Cluster
TextOllama2023–2026
DeepSeek · China
DeepSeek's flagship line: from the first 7B/67B to V4-Pro with 1.6 trillion parameters. Closed-model quality under an open MIT license; V4-Flash-Vision-Exp and V4.1-Flash understand images, context up to 1M tokens. The fresh V4.1-Flash-1017 answers shorter and faster than the previous Flash: by the measurements of DeepSeek itself, 77.0 vs 74.2 on DeepSWE v1.1 and 42.3 vs 31.2 on Terminal-Bench 4.0.
- Employee assistant on your own server
- Analysis of long contracts and reports
- Agents that work with tools and APIs
- Sizes
- 7B – 1.6T-A49B
- Hardware
- from: Laptop
Search and RAG2026
OpenBMB · China
Embeddings for mixed-modality search: text, images and pages with text and a picture together land in one space, and a single text query can rank them in one shared list. Built on research showing that ordinary models prefer text over images. Language on the card: English.
- searching a catalog where some items are described by text and some by a picture
- searching slide decks and pages with diagrams
- RAG over a mixed knowledge base
- Sizes
- 2B (based on Qwen3-VL-2B)
- Hardware
- from: Laptop
Text analysis2026
Mistral AI · France
Quickly identifies the language and dialect of text in Arabic script: Modern Standard Arabic, all dialects and 51 classes overall. It tells apart close languages in the same script (Persian, Urdu, Pashto and others) so that a text is not called Arabic just because of its letters. Runs on a CPU.
- detecting the dialect in customer requests in Arabic
- sorting texts by language in Arabic script
- preparing data for training and search
- Sizes
- a fastText model with calibration, parameter count not stated
- Hardware
- from: Laptop
Video2026
Fudan University, Tencent Hunyuan and Zhejiang University · China
Creates video together with sound: from a first frame and a description you get a clip with speech, effects and music. Native generation at 720p, 1080p and 2K is stated. In the third-party FreeVideo build (1280 by 720, 8.5 seconds) it runs on one RTX 30, 40 or 50 series card with 12 GB or more, but it will not be fast.
- animating a picture into a clip with sound
- ad and training videos with voice-over
- prototypes of scenes for video and animation
- Sizes
- not stated on the card (based on MOVA-360p)
- Hardware
- from: 1 GPU
Image generation2026
Sperid Labs · not stated
Generates images directly in pixels, without a compressed latent space. After fine-tuning, the same weights estimate depth from a single photo and restore and upscale images 4 times. Prompts are in English, the default size is 1024 by 1024.
- generating images from a description
- estimating scene depth from a single photo
- restoring and upscaling old or compressed photos
- Sizes
- 3B
- Hardware
- from: 1 GPU
Text2026
Shanghai Artificial Intelligence Laboratory · China
An agent model for long tasks: searching and gathering evidence, research, development, preparing reports and presentations, analyzing vulnerabilities in an authorized environment. A preview based on GLM-5.2, 256K-token context, text only. An FP8 version exists.
- deep search and research on a topic with a verifiable result
- developing programs and preparing reports and presentations
- checking and fixing vulnerabilities in an authorized environment
- Sizes
- 744B (MoE, based on GLM-5.2)
- Hardware
- from: Cluster
Visual document searchGGUF2026
Tencent · China
Finds the right pages in documents as pictures, without turning them into text: matches a query against how the page looks. Version 8B scores 66.75 on ViDoRe V3. The index can be compressed to 32 vectors per page.
- searching scans, slides and reports without text recognition
- RAG over documents with tables and charts
- searching archives of contracts and catalogs
- Sizes
- 4.5B и 8B
- Hardware
- from: Laptop
Code2026
Microsoft · USA
A compact agent for working with repository code, based on Qwen3.5-4B: searches the project, edits files, runs tests and prepares a patch. Trained only with reinforcement learning on about 1500 synthetic tasks. Works through the light Leaf harness with five tools.
- fixing bugs in a repository from a task description
- navigating an unfamiliar codebase
- preparing patches with test runs
- Sizes
- 4B
- Hardware
- from: Laptop
Text analysis2026
Shanghai Artificial Intelligence Laboratory · China
A decision model based on Qwen3.5-4B: from text and images it answers all questions about a situation with probabilities in one pass, without generating text. Suits routing requests and rating urgency.
- routing requests to teams
- rating priority and urgency of requests
- checking from a photo that everything is in order
- Sizes
- 4B
- Hardware
- from: Laptop
Tabular data2026
NVIDIA · USA
A pretrained model for tables: classification and regression from in-context examples, with no task-specific training. You supply labeled rows and the rows that need a forecast and get class probabilities.
- scoring customers and requests
- forecasting from a table of sales or orders
- detecting churn from a customer table
- Sizes
- size not stated on the card
- Hardware
- from: Laptop
Medicine2026
NVIDIA · USA
A language model for computed tomography: looks at a whole chest or abdominal CT volume, not separate slices, writes structured reports and answers questions with reasoning. English only.
- a draft CT report for a physician
- yes-or-no answers about a scan with reasoning
- research in medical imaging
- Sizes
- 4B (based on Qwen3.5-4B with a 3D encoder)
- Hardware
- from: 1 GPU
Documents and OCR2026
Tencent · China
Parses a whole document page: turns it into Markdown with LaTeX formulas and HTML tables. The 4B version scores 95.38 on OmniDocBench v1.6. Languages on the card: English and Chinese.
- turning scans and PDFs into Markdown for search and RAG
- recognizing tables and formulas
- parsing reports and scientific papers
- Sizes
- 2B и 4B
- Hardware
- from: Laptop
Computer-use agents2026
Tencent · China
An open agent for operating a desktop: looks at live screenshots, reasons and outputs clicks and keyboard input. You can show a workflow once and the agent carries it over to a new task. An external environment is needed to execute the actions.
- automating work in programs with no API
- repeating a workflow from one shown example
- testing interfaces
- Sizes
- 27B
- Hardware
- from: 1 GPU
Search and RAG2026
Tencent · China
Universal embeddings based on Qwen3.5: they turn text, images, video and visual documents into one vector of 4096 numbers. Audio is not supported. Languages on the card: Chinese and English.
- searching a product catalog by picture or description
- searching video and slide decks
- RAG over mixed text and image materials
- Sizes
- 2B и 9B
- Hardware
- from: Laptop
Computer-use agents2026
Beijing Academy of Artificial Intelligence (BAAI) · China
An agent model of 27B (based on Qwen3.8-27B) for long tasks: it proposes a solution, measures the result, analyzes errors and revises the solution over several rounds. A 262K-token context. Stated as a research model.
- iterative improvement of code and algorithms
- machine learning tasks with a verifiable result
- deep search and gathering information on a topic
- Sizes
- 27B
- Hardware
- from: 1 GPU
Speech to text2026
Cactus Compute · not stated
Speech recognition in a single 16.9 MB file: runs on a phone, watch, robot and CPU without a graphics card. Languages: English, German, French, Spanish, Italian, Dutch, Polish. Gives word timestamps.
- voice input in mobile apps without internet
- controlling a device by voice
- highlighting words in subtitles by timestamps
- Sizes
- 16.9 MB
- Hardware
- from: Laptop
Text2026
Ai2 (Allen Institute) · USA
An 8B model that turns a question and the excerpts of scientific papers you give it into a report with citations. It does not search by itself: excerpts must be supplied with the question.
- literature overview with source citations
- summary of your own set of PDFs
- draft analytical note with quotes
- Sizes
- 8B
- Hardware
- from: Laptop
Text analysis2026
AutoTrust AI · Singapore
Open decision models: for yes/no, pick-one and rate-0-to-5 questions they answer with probabilities in one pass, and can also reason when needed. Not affiliated with the closed Jev from TypeSafe.
- routing requests to the right team
- checking an agent action before it runs
- rating urgency and tone of messages
- Sizes
- 9B – 35B
- Hardware
- from: 1 GPU
Text2026
Aleph Alpha · Germany
A European open reasoning model for German and English. A 78B mixture-of-experts with 3.5B active per token, a 262K-token context (tested up to a million) and tool calling.
- answers over long documents and RAG
- an agent that calls tools
- extracting structured data from documents
- Sizes
- 78B-A3.5B
- Hardware
- from: Cluster
Text analysis2026
Perplexity · USA
A decision model built on Qwen3.8-27B: it picks an option, answers yes or no or gives a rating, and returns calibrated probabilities. It also understands images.
- routing requests to teams
- checking AI answers against sources
- rating tone and urgency of emails
- Sizes
- 27B
- Hardware
- from: 1 GPU
Speech to text2026
Edge0 · not stated
Streaming recognition of Chinese and English speech with a 240-560 ms delay. It can listen indefinitely without memory growth and tells a thinking pause from the end of a turn.
- subtitles for live streams and calls
- voice assistants with fast reaction
- round-the-clock transcription of a speech stream
- Sizes
- 4B
- Hardware
- from: 1 GPU
Text analysis2026
Supersonic Labs · not stated
A very small decision model: from a text, a question and answer options it picks one option, gives a rating or answers yes or no. Runs on an ordinary CPU and in the browser.
- routing requests by topic
- detecting the tone of reviews
- fast classification of requests
- Sizes
- 144M
- Hardware
- from: Laptop
Speech to text2026
Fermion Research · not stated
A very compact English speech recognition model: 164 MB, close in accuracy to its large Parakeet base. Transcribes an hour of audio in about 20 seconds on a laptop.
- transcribing English meetings and calls
- dictating text on a laptop offline
- subtitles for English videos
- Sizes
- 164 MB (about 2.1 bits per weight)
- Hardware
- from: Laptop
Text analysisOllama2026
Cloudflare · USA
Decision models: they do not write text but read a situation (text, JSON, an image, video frames, and for Clef-Omni also audio) and return in one pass the probability of each answer to typed questions: yes or no, pick one, rate on a scale. The agent gets ready numbers instead of parsing free text.
- sorting requests and tickets into categories with a probability
- checking a document or photo against a list of questions (is everything stated, is there a violation)
- choosing the next step of an agent without parsing a text answer
- Sizes
- 27B, 9B (Clef-flash) and 30B-A3B (Clef-Omni)
- Hardware
- from: Laptop
Documents and OCRGGUF2025–2026
LightOn · France
A French OCR model that converts a page into text in one pass and is fast on high volumes. The third generation (0.8B, 1B, 4B) also returns block coordinates, image descriptions and chart data as a table. Languages on the version 2 card: European languages, Chinese and Japanese; no Russian.
- Recognising invoices and contracts in European languages
- Table recognition
- Converting PDFs to text for search and RAG
- Sizes
- 0.8B – 4B
- Hardware
- from: Laptop
Image + textOllama2024–2026
OpenBMB (ModelBest and Tsinghua University) · China
Compact vision models that run even on a phone or laptop. Good at reading text in photos and understanding video; version 4.6 is only 1.3B. The fresh 4.7 comes in two sizes, 1B and 35B-A3B, the first MoE model in the family. According to the authors, 35B-A3B runs on an iPhone 17 Pro Max at 13+ tokens per second with 3 GB of memory thanks to their way of loading experts. The figures come from the authors themselves.
- On-device text recognition in photos
- Processing receipts and documents without sending them to the cloud
- Describing photos and video
- Sizes
- 1B – 35B-A3B
- Hardware
- from: Laptop
Autonomous driving2020–2026
comma.ai · USA
An open driver assistance system: a neural network keeps the lane and controls speed from a camera, plus a driver attention monitoring model. The models live right in the repository and are updated constantly.
- A research testbed for driver assistance systems
- Studying driver attention monitoring with an in-cabin camera
- Comparison with your own lane-keeping algorithms
- Sizes
- compact, designed for an in-vehicle device
- Hardware
- from: Laptop
Text analysis2026
FlowX.AI · USA and Romania
A family of small models that pull amounts, deal parties, jurisdictions, accounts and sanctions-screening mentions out of banking and insurance texts. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
- Extracting amounts, parties and jurisdictions from operation descriptions
- Parsing customer due diligence material and sanctions lists
- Marking account numbers and payment details in documents
- Sizes
- about 150M (based on ModernBERT-base)
- Hardware
- from: Laptop
Text analysisGGUF2026
FlowX.AI · USA and Romania
Small models from a banking software company that read the text of an SMS, email or chat message and explain which scam tactic it uses. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
- Flagging incoming messages that show signs of deception
- Explaining which phrase triggered the flag
- Filtering emails and messages before they reach an operator
- Sizes
- 0.6B – 1.7B
- Hardware
- from: Laptop
TextRU2024–2026
Sber · Russia
Sber open models with strong Russian language support and local context, from 10B-A1.8B to 702B, all MIT. GigaChat3.1-Audio handles recordings up to two hours; GFusion is a fast diffusion text version.
- Russian-language employee assistant on your own server
- Customer replies and request handling in Russian
- Working with contracts and internal policies
- Sizes
- 10B-A1.8B – 702B-A36B
- Hardware
- from: Laptop
Text analysis2024–2026
Urchade Zaratiana and Fastino AI · France / USA
Finds the entities you need in text without training: just list what to look for (name, amount, date). GLiNER2 also classifies text. Multilingual versions understand Russian.
- Extracting names, amounts and dates from emails and contracts
- Parsing requests into CRM fields
- Classifying requests by topic
- Sizes
- about 50M to 500M
- Hardware
- from: Laptop
Drawings and CADRUGGUF2026
GreenMap · not disclosed
A set of small models for Russian-language construction drawings: it finds the drawing area, title block and legend, marks up walls and hatching, and pulls sheet data into JSON along with references to standards. A draft that an engineer checks.
- Finding the title block, legend and drawing area on a sheet
- Marking up walls and hatching on a floor plan
- Extracting drawing data into structured JSON
- Sizes
- 3.5M - 4B
- Hardware
- from: Laptop
Music and sound2026
HeartMuLa Team · not disclosed
An open model for generating songs with vocals in Chinese, English, Japanese, Korean and Spanish, plus a codec and a lyrics transcription model.
- Songs and jingles from lyrics
- Music for videos
- Transcribing song lyrics
- Sizes
- 3B
- Hardware
- from: 1 GPU
MedicineGGUF2023–2026
FreedomIntelligence (The Chinese University of Hong Kong, Shenzhen) · China
A large family of medical models: chat, an imaging version, the reasoning HuatuoGPT-o1 and the new HuatuoGPT-3 on Qwen3. Does not replace a doctor; decisions are made by a specialist.
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Hints for doctors when reviewing images (Vision)
- Sizes
- 7B – 72B
- Hardware
- from: Laptop
Plates and vehicles2026
Intel · USA
Intel models for vehicle video analytics: car, truck, bus, motorcycle, plus entry and exit logging and vehicles stopped too long. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Counting vehicles and splitting them by type
- Logging vehicle entry and exit
- Monitoring parking space occupancy
- Sizes
- YOLO26 variants from nano to x
- Hardware
- from: Laptop
TextOllama2023–2026
Shanghai AI Laboratory · China
Models from Shanghai AI Laboratory. The early InternLM line is general-purpose; the new Intern-S1/S2 is scientific: it understands formulas, molecules, charts and images.
- Research assistant: papers, formulas, data
- Analysis of scientific and technical documents
- Corporate chat on small models
- Sizes
- 1.8B – about 1T
- Hardware
- from: Laptop
Text2024–2026
MBZUAI, Institute of Foundation Models (IFM, LLM360 project) · UAE
Fully open models from the UAE: data, training code and intermediate checkpoints are published along with the weights. K2-Horizon (2026) spans 0.9B to 375B with context up to 512K tokens.
- Reasoning, maths and technical questions
- Analysing long documents
- Agents and writing code
- Sizes
- 0.9B – 375B-A23B
- Hardware
- from: Laptop
Math and reasoning2026
Paradigma · not disclosed
A 1B model that does exactly one thing: it solves maths problems. It answers in a single turn, with no dialogue, and handles non-maths questions poorly. A companion Value Model scores someone else's solution step by step.
- Solving maths problems in a single answer
- Picking the best solution out of several candidates
- Scoring reasoning step by step when training another model
- Sizes
- 1B
- Hardware
- from: 1 GPU
TextGGUF2025–2026
Renmin University of China (GSAI) and Ant Group (inclusionAI) · China
Diffusion language models: text is written in blocks and then refined rather than word by word, which speeds up generation. LLaDA2.2 can edit what it has written and targets agents. LLaDA-Image is a separate product.
- Fast generation of code and text
- Agent scenarios with long context
- Research into alternatives to standard LLMs
- Sizes
- 8B – 100B (MoE)
- Hardware
- from: 1 GPU
CodeGGUF2025–2026
JetBrains · Czech Republic
JetBrains models for fast code autocompletion. Mellum2 (12B, 2.5B active) is already a full assistant: it writes and edits code, calls tools and reasons. Version 2.1 spent most of its training on reinforcement learning in real repositories with a shell and tests: 47 on SWE-bench Verified, self-reported by JetBrains.
- Fast code autocompletion on your own server
- A developer assistant that does not send code to the cloud
- Fine-tuning on the company's code
- Sizes
- 4B – 12B-A2.5B
- Hardware
- from: Laptop
TextGGUF2025–2026
Xiaomi · China
Xiaomi models for reasoning and agents: from the compact MiMo-7B to MiMo-V2.6-Pro with 1.02 trillion parameters. The larger versions understand text, images, video and audio, with a 1M token context. Languages: English and Chinese.
- Logic and calculation tasks
- Agents with tools
- Help for developers
- Sizes
- 7B – 1,02T-A42B
- Hardware
- from: Laptop
Text2024–2026
OpenBMB (ModelBest and Tsinghua University) · China
Compact text models that run directly on a device: laptop, phone or mini PC. The 1B and 2B MiniCPM5 models focus on tool calling and long context.
- A local chat assistant without the cloud
- Data extraction and text classification
- Tool calling and simple agents on low-end hardware
- Sizes
- 0.5B – 8B
- Hardware
- from: Laptop
Tabular data2025–2026
Amazon (AutoGluon team) · USA
Amazon's tabular model built into AutoGluon: classification and regression from examples with brief fine-tuning. Mitra-v2 handles more rows and columns.
- Predicting churn and repeat purchases
- Scoring applications
- Predicting deal or order value
- Sizes
- about 76M
- Hardware
- from: Laptop
Voice: speakers and soundGGUF2026
NVIDIA · USA
Marks up a recording by speaker: who spoke when, for up to eight participants, both in files and live. The model is small, ships a GGUF build and runs without a GPU. Call recordings are personal data, so retention rules are agreed with a lawyer.
- Splitting a call or meeting recording by participant
- Adding speaker names to a transcript
- Live speaker labelling during a conversation
- Sizes
- 100M
- Hardware
- from: Laptop
Search and RAGGGUF2026
Perplexity · USA
Embeddings from the Perplexity search service. Some versions take into account the context of the whole document, not just a single fragment.
- Search across large document collections
- RAG that accounts for document context
- Website and catalog search
- Sizes
- 0.6B – 9B
- Hardware
- from: Laptop
Tabular data2025–2026
Layer 6 AI (TD Bank) · Canada
A tabular model from a Canadian bank's AI lab, trained on real tables rather than only synthetic ones. Version 1.2 Turbo made computation orders of magnitude faster.
- Scoring applications and customers
- Predicting churn
- Classifying transactions and customers
- Sizes
- about 60–80M
- Hardware
- from: Laptop
Deepfake detection2023–2026
Adobe Research and University of Surrey · USA
An image watermark for arbitrary resolutions built for the Content Authenticity Initiative: it can both apply a mark and remove one. The detector errs in both directions - a human reviews the output.
- Marking images on the way out of your own pipeline
- Checking the provenance of a submitted image
- Linking with content provenance metadata
- Sizes
- model types Q and P with different mark capacity
- Hardware
- from: Laptop
Speech to textRUGGUF2025–2026
Microsoft · USA
Microsoft speech models: long multi-voice dialogue synthesis, fast synthesis for live conversation, and recognition of long recordings split by speaker, including in Russian.
- Transcribing long meetings with speaker labels
- Voicing podcasts and dialogues
- Real-time voice for assistants
- Sizes
- 0.5B – 9B
- Hardware
- from: Laptop
Acoustic monitoring2019–2026
Google · USA
A tiny model covering 521 sound events, including alarms, breaking glass and screams: it fits on a microcontroller and runs without a GPU. A microphone can capture people voices, which is personal data, so check the procedure with a lawyer.
- Fast sound labelling right on the device
- Detecting alarm sounds on a site
- Picking interesting fragments out of a continuous recording
- Sizes
- 3.7M
- Hardware
- from: Laptop
TextRU2026
SberDevices (ai-forever) · Russia
A Russian and English research prototype: the model writes text in blocks at once (diffusion) rather than word by word, which speeds up responses. The authors do not recommend it for production systems.
- Experiments with faster generation
- Fine-tuning small models for your own tasks
- Research
- Sizes
- 0.6B – 4B
- Hardware
- from: Laptop
Drawings and CAD2026
FusionBrain Lab, Lomonosov Moscow State University and Innopolis University · Russia
It writes CadQuery code from images and a point cloud, then edits its own output over several rounds, comparing the resulting shape with the original. This is a draft model: an engineer checks and signs off the document.
- Recovering a parametric model from photos and a scan of a part
- Step-by-step refinement of a draft CAD model
- Digitising parts that have no drawings
- Sizes
- 2.2B
- Hardware
- from: Laptop
Deepfake detection2025–2026
University of Michigan · USA
A lightweight detector of generated images, trained on 2.7M samples from nearly 5000 different generators. It errs in both directions: the result is a reason for a human to check, not proof.
- Checking submitted photos and illustrations
- Filtering AI images in a content flow
- Flagging suspicious images for manual review
- Sizes
- 22M
- Hardware
- from: Laptop
Search and RAGRU2024–2026
Sber (SberDevices) · Russia
Sber embeddings built for Russian: according to the developers, among the best on Russian-language search benchmarks. FRIDA is compact, Giga-Embeddings is more powerful.
- Search across Russian-language documents
- RAG for chatbots in Russian
- Classifying requests and reviews
- Sizes
- 480M – 10B-A1.8B
- Hardware
- from: Laptop
Robotics2025–2026
GigaAI · China
A robot control model trained mostly on synthetic data from a world model. It reduces spending on collecting data from real robots.
- Controlling a robot arm
- Fine-tuning on a small amount of your own data
- Sorting and assembly pilots
- Sizes
- 3.5B
- Hardware
- from: 1 GPU
Weather and climate2023–2026
Google DeepMind · UK
Google DeepMind's family of global weather models: GraphCast (10-day forecast), GenCast (probabilistic ensemble) and WeatherNext 2 with cyclone forecasting. Since August 2026 the weights are cleared for commercial use.
- Medium-range weather forecasts for planning shifts, voyages and deliveries
- Probabilistic assessment of extreme weather for insurance portfolios
- Tropical cyclone track forecasts for marine and port operations
- Sizes
- from lightweight 1° versions to full 0.25°
- Hardware
- from: 1 GPU
Speech to textGGUF2025–2026
IBM · USA
IBM speech models for recognizing and translating speech in English, several European languages and Japanese. Designed for enterprise use.
- Transcribing business meetings
- Translating speech into text in another language
- Voice assistants
- Sizes
- 470M – 8B
- Hardware
- from: Laptop
TextOllama2024–2026
IBM · USA
IBM enterprise models with transparent training data and ISO 42001 certification. Granite 4 is a memory-efficient Mamba and Transformer hybrid.
- Answers based on internal documents (RAG)
- Tool calling and agent work
- Data extraction and classification
- Sizes
- 350M – 34B
- Hardware
- from: Laptop
VideoGGUF2025–2026
Sand AI · China
Video generated chunk by chunk in sequence, so a clip can be extended indefinitely. MAGI-2 produces video with sound.
- Long videos with continuation
- Video with sound
- Animating images
- Sizes
- 4.5B – 114B-A6B
- Hardware
- from: 1 GPU
Acoustic monitoring2021–2026
MLCommons · USA
A reference autoencoder for finding anomalies in machine sound: it learns only from recordings of a healthy unit and flags deviations. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- Listening to a machine tool, pump or conveyor
- Flagging deviations from a unit usual noise
- Training on your own recordings of healthy equipment
- Sizes
- a tiny fully connected autoencoder sized for microcontrollers
- Hardware
- from: Laptop
Computer vision2024–2026
Microsoft Research · USA
Reconstructs the 3D geometry of a scene from one photo: depth in meters, a point cloud and surface normals.
- Measuring rooms and objects from photos
- 3D point cloud from a single shot
- Preparing data for robots and AR
- Sizes
- ViT-S – ViT-G
- Hardware
- from: Laptop
Speech to textGGUF2024–2026
Moonshine AI (Useful Sensors) · USA
Very small and fast speech recognition models for phones, tablets and embedded devices. Version 2 streams, producing text while the person is still speaking.
- Voice control of devices
- Offline recognition on a phone
- Live subtitles
- Sizes
- 27M – 245M
- Hardware
- from: Laptop
TextOllama2026
Meta Superintelligence Labs · USA
An open Meta model for agents on affordable hardware: distilled from the closed Muse Spark, understands text and images, trained on 100+ languages.
- Agents with tool calling
- Analysis of screenshots, charts and documents
- Multilingual assistant
- Sizes
- 30B
- Hardware
- from: 1 GPU
Computer-use agents2025–2026
XLANG Lab (University of Hong Kong) · China
Fully open desktop agents: weights, data and training code. They work on Windows, macOS and Linux; the latest Qwen-CUA controls a computer with ordinary clicks and keystrokes.
- Working in desktop software without an API
- Moving data between systems
- Running user scenarios for tests
- Sizes
- 7B – about 400B (MoE)
- Hardware
- from: 1 GPU
Biology and chemistry2022–2026
AlQuraishi Lab (Columbia University) and the OpenFold consortium · USA
A fully open reproduction of AlphaFold 2 and then AlphaFold 3 under Apache 2.0, with training data. OpenFold3 predicts complexes of proteins, nucleic acids and ligands.
- Predicting structures of proteins and ligand complexes
- Fine-tuning on the company's own data (training code is open)
- An in-house structural analysis service without sending data outside
- Sizes
- a single set of weights per version
- Hardware
- from: 1 GPU
Autonomous driving2026
Alibaba (Qwen team) · China
An autonomous driving model based on Qwen3.5-4B: 3D detection of objects around the vehicle, answers to questions about the road scene and trajectory planning in one model.
- A perception and planning prototype for autonomous vehicles on closed sites
- Answering questions about camera recordings when reviewing incidents
- Labeling road scenes to train your own models
- Sizes
- 4B
- Hardware
- from: 1 GPU
Video2025–2026
NVIDIA · USA
NVIDIA's lightweight, fast video model. Produces 720p clips on a single GPU; a 4-step version enables quick generation.
- Quick clips for social media
- Bulk video generation
- Video from an image
- Sizes
- 2B – 5B
- Hardware
- from: 1 GPU
Documents and OCR2026
TeleAI (China Telecom) · China
A new lightweight document parsing model that led the OmniDocBench v1.6 benchmark at release. Handles pages photographed on a phone and crumpled pages well. Languages on the card: Chinese, English, Japanese.
- Recognising invoices and delivery notes photographed on a phone
- Recognising tables and formulas
- Converting documents to Markdown for RAG
- Sizes
- about 1.2B
- Hardware
- from: Laptop
Deepfake detection2023–2026
University of Wisconsin-Madison · USA
An early and still used approach: a simple classifier trained on top of a frozen CLIP that transfers to unseen generators. It errs in both directions - the output needs a human check.
- Checking images from new, unfamiliar generators
- A baseline when comparing detectors
- Fast rollout of a check without training a large model
- Sizes
- a linear classifier on top of CLIP ViT-L/14
- Hardware
- from: Laptop
TextRUGGUF2025–2026
Swiss AI (ETH Zurich, EPFL, CSCS) · Switzerland
Switzerland's public open model: weights, data and recipe are open, with more than 1000 languages in training. Version 1.5 understands images.
- Multilingual assistant
- Answers based on documents
- Analysis of images and scans (v1.5)
- Sizes
- 0.5B – 70B
- Hardware
- from: Laptop
Voice: speakers and sound2022–2026
Meta AI, then Alexandre Défossez · France
A classic model that splits a track into vocals, drums, bass and the rest. The v4 hybrid transformer version remains the benchmark; the project is now maintained by its author in his own repository.
- Separating vocals from music in a recording
- Backing tracks and karaoke stems
- Cleaning speech in videos with background music
- Sizes
- tens of millions of parameters
- Hardware
- from: Laptop
Computer-use agentsGGUF2025–2026
Microsoft · USA
Small Microsoft models for working in the browser: they look at the page and click, type and scroll. Designed to run directly on a work computer without the cloud.
- Filling in web forms and applications
- Collecting data from web portals without an API
- Checking websites against scenarios
- Sizes
- 4B – 27B
- Hardware
- from: Laptop
Speech to textRUGGUF2024–2026
Sber · Russia
Sber's models for Russian speech recognition, among the most accurate for Russian. Includes emotion recognition, v3 with punctuation, and a multilingual version (Russian, Kazakh, Kyrgyz, Uzbek).
- Transcribing calls in Russian
- Meeting minutes
- Voice control of services
- Sizes
- 220M – 600M
- Hardware
- from: Laptop
TextGGUF2026
Thinking Machines Lab · USA
Flagship open models from Mira Murati's lab: they take text, images and audio. Large MoE models that need several GPUs.
- Flagship-level corporate assistant
- Analysis of documents, images and audio
- Programming help
- Sizes
- 276B-A12B, 975B-A41B
- Hardware
- from: Cluster
Code2025–2026
Kwaipilot (Kuaishou) · China
Kuaishou models for agentic development, trained to solve real tasks in repositories. KAT-Coder-V2.5-Dev (35B, 3B active) is the open version of their closed flagship.
- An agent that fixes tasks in the repository
- Code generation and refactoring
- Automating routine development tasks
- Sizes
- 32B – 72B, 35B-A3B
- Hardware
- from: 1 GPU
CodeGGUF2026
Poolside · USA
Models for agentic programming: they edit code in a repository on their own. The small XS runs on a Mac with 36 GB of memory; S 2.1 has a 1M-token context.
- Coding agent for in-house development
- Bug fixing and code improvements
- Working with large codebases
- Sizes
- 33B-A3B – 225B-A23B
- Hardware
- from: 1 GPU
Robotics2026
Ant Group (Robbyant) · China
A robot control model from Ant Group trained on a large volume of data from real robots. Version 2.0 works with different types of robot arms.
- Controlling a two-armed robot
- Fine-tuning for your own operation
- Assembly and sorting pilots
- Sizes
- 4B – 6B
- Hardware
- from: 1 GPU
TextGGUF2025–2026
Meituan · China
Models from Meituan, China's largest delivery service. LongCat-Flash adjusts compute to query complexity; LongCat-2.0 has 1.6 trillion parameters under MIT. Omni models (Flash-Omni, Next) and AudioDiT speech synthesis too.
- Agents for orders and service processes
- Corporate assistant
- Analysis of long documents
- Sizes
- 1B – 1.6T-A48B
- Hardware
- from: Laptop
Weather and climate2024–2026
Microsoft Research · USA
A foundation model of Earth's atmosphere: global weather forecasts, plus separate versions for air quality and ocean waves. Computes a forecast in seconds instead of hours on a supercomputer.
- Your own forecast of temperature, wind and precipitation for company locations
- Sea state estimates for planning voyages and port operations
- Air pollution forecasts for industrial sites
- Sizes
- about 1.3B (a small test version is available)
- Hardware
- from: 1 GPU
Image + text2026
OpenMOSS (Fudan University) · China
An image + video + text model focused on long videos and precise linking of events to timestamps. A Realtime version handles live video streams.
- Analyzing long videos and finding events by time
- Real-time streaming video analysis
- Understanding photos and documents
- Sizes
- about 11B
- Hardware
- from: 1 GPU
RecommendersGGUF2025–2026
Kuaishou · China
An open foundation model for recommendations from a short-video service: browsing and purchase history is fed to the model as a sequence and it predicts the next item or clip. Fine-tuning on your own data is required.
- A personal feed of products or content
- Picking the next item from order history
- Recommendations inside ad slots
- Sizes
- 1.7B, 8B
- Hardware
- from: Laptop
Plates and vehicles2024–2026
ankandrew (open project) · not disclosed
Ready-made ONNX detectors that find the license plate in a frame, plus general object detectors. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Finding the plate in a camera frame
- Preparing a crop for character reading
- Picking frames with vehicles out of a video stream
- Sizes
- YOLO-v9 detectors at input sizes from 256 to 640 pixels
- Hardware
- from: Laptop
Image + textGGUF2024–2026
Alibaba (AIDC-AI) · China
Vision models from Alibaba's international division with strong text and table reading. The line includes the Ovis2.6 MoE and separate compact OvisOCR models for documents.
- Extracting data from invoices, contracts and delivery notes
- Table recognition
- Answering questions about photos and charts
- Sizes
- 0.9B – 80B-A3B
- Hardware
- from: Laptop
Rerankers2026
Tencent · China
A pair of small Tencent models based on Qwen3 that pick the right skill for an AI agent for a given request: the embedding model finds candidates, the reranker chooses the best one.
- Choosing a tool or skill for an AI agent
- Routing requests between bot scenarios
- Search across a catalog of internal tools
- Sizes
- 0.6B
- Hardware
- from: Laptop
Voice: speakers and sound2023–2026
RVC-Project community · China
The most widely used open voice conversion tool: a model for a specific voice trains on 10–30 minutes of recording and works in real time. Use only with the voice owner's consent.
- Voicing content with one brand voice
- Covers and vocal work
- Real-time voice changing
- Sizes
- tens of millions of parameters
- Hardware
- from: Laptop
TextRU2024–2026
T-Bank · Russia
T-Bank models fine-tuned from Qwen for Russian: they write and reason in Russian noticeably better than the original. T-Lite is 8B, T-Pro 32B on one GPU; T-Search is a multi-step search agent in Russian and English.
- Russian-language support chatbot
- Analysis of requests and documents in Russian
- Answers based on the company knowledge base
- Sizes
- 7B – 36B-A3B
- Hardware
- from: Laptop
Video2025–2026
Alibaba · China
Text-to-video and image-to-video; the small version runs on a gaming GPU. After 2.2 only applied models are open: editing (VACE), audio-driven talking characters (S2V), dancing to music (Dancer).
- Short promo videos
- Animating product photos
- Videos for social media
- Sizes
- 1,3B – 14B
- Hardware
- from: 1 GPU
Voice: speakers and soundGGUF2022–2026
WeNet community · China
A set of ready-made voiceprint models: checks whether the same person speaks in two recordings and helps split a recording by speaker. One of the models is built into pyannote 3.x.
- Voice verification of a customer during a call
- Finding repeat calls from the same person
- Splitting a recording by speaker
- Sizes
- from a few to tens of millions of parameters
- Hardware
- from: Laptop
Robotics2026
Xiaomi · China
Open robot control models from Xiaomi. Robotics-1 is designed for household and kitchen tasks, U0 combines scene understanding and action.
- Controlling a robot arm by command
- Household and service scenarios
- Base for fine-tuning
- Sizes
- 4B – 5B
- Hardware
- from: 1 GPU
Music and soundRUGGUF2025–2026
ACE Studio and StepFun · China
Fast generation of songs with vocals in 19 languages, including Russian: a full song in seconds, editing of individual parts and style changes.
- Songs and jingles for ads
- Background music for videos
- Demo versions of tracks
- Sizes
- about 2B – 4B
- Hardware
- from: Laptop
Speech to textGGUF2026
Cohere · Canada
Cohere's speech recognition model for 14 languages (Russian is not on the list), with a separate version for Arabic. Built for accurate transcription of business recordings.
- Transcribing meetings and interviews
- Subtitles
- Searching an audio archive
- Sizes
- 2B
- Hardware
- from: Laptop
TextOllama2024–2026
Google · USA
Compact Google models that run well on a single computer; larger versions understand images. Includes CodeGemma for code, FunctionGemma 270M for function calling and the fast DiffusionGemma.
- Offline assistant on a laptop
- Reading photos of documents and receipts
- Customer request classification
- Sizes
- 270M – 31B
- Hardware
- from: Laptop
Moderation and safety2024–2026
GLiNER community (Fastino, Knowledgator, NVIDIA and others) · USA
Small GLiNER-based models for finding personal data: passports, phone numbers, accounts, addresses. Data types are set in words. Russian is not officially supported.
- Masking personal data before cloud AI
- Finding passport data and bank details in documents
- Checking data exports for leaks
- Sizes
- about 200M to 500M
- Hardware
- from: Laptop
Image + text2023–2026
Shanghai AI Lab (OpenGVLab) · China
A family of video models: encoders for search and classification of clips, and chat models that analyze long videos. InternVideo 3 is designed for multi-hour recordings.
- Searching a video archive with a text query
- Action recognition in video
- Answering questions about a long recording
- Sizes
- small encoders – 9B
- Hardware
- from: Laptop
Math and reasoningOllama2025–2026
Open Thoughts (Stanford, Berkeley and other universities) · USA
Fully open reasoning models: both weights and training data are published. Newer OpenThinkerAgent versions can carry out multi-step tasks.
- Calculations and formula checks
- Complex analytics with step-by-step breakdowns
- Checking the logic of internal policies
- Sizes
- 1.5B – 32B
- Hardware
- from: Laptop
Acoustic monitoring2019–2026
University of Surrey · UK
The classic set of convolutional networks that label sound across the 527 AudioSet categories, from machinery noise and alarms to breaking glass and screams. The system does not make a diagnosis, it gives you a reason to check the unit before it fails. A microphone can also capture people voices, which is personal data, so check the procedure with a lawyer.
- Labelling what is happening in a microphone recording
- Detecting alarms, breaking glass, screams
- A base for your own model tuned to one shop floor
- Sizes
- from 5.9M (CNN6) to 81.9M (CNN14)
- Hardware
- from: Laptop
Documents and OCRRU2022–2026
Baidu (PaddlePaddle) · China
Classic lightweight PaddleOCR models: detecting and recognizing lines of text plus page layout. They run on CPUs and phones; there is a separate model for East Slavic languages, including Russian.
- Recognizing text on scans, photos and screens
- Reading labels, displays and markings in production and warehouses
- Page layout: tables, formulas, stamps, headings
- Sizes
- from 1.5M to tens of millions of parameters
- Hardware
- from: Laptop
Speech to textRUGGUF2026
Alibaba (Qwen) · China
Speech recognition models from the Qwen team for 50+ languages, including Russian. They handle noise, singing and accents well.
- Transcribing calls and meetings
- Video subtitles
- Multilingual recognition
- Sizes
- 0.6B – 1.7B
- Hardware
- from: Laptop
Computer vision2025–2026
Roboflow · USA
Real-time object detector, an open alternative to YOLO without AGPL. Supports segmentation (object outlines) and, since 2026, keypoints.
- Object detection in video and photos
- Precise outlines of parts and defects
- Fine-tuning for your own object classes
- Sizes
- Nano – 2XL
- Hardware
- from: Laptop
VideoGGUF2025–2026
Zhipu AI (Z.ai) and Tsinghua University · China
Animates a character from an image using motion from another video, including complex turns and multiple characters. SCAIL-2 works without an intermediate skeleton and can replace a character in a clip.
- Transferring an actor's motion to a character
- Replacing a character in a finished video
- Animating mascots and illustrations
- Sizes
- 14B
- Hardware
- from: 1 GPU
Forecasting2025–2026
NXAI · Austria
A compact forecasting model on the xLSTM architecture, a leader in open benchmarks despite its small size. Runs fast on a regular CPU.
- Demand and sales forecasting
- Energy consumption forecasting
- Forecasts on modest hardware and on site
- Sizes
- about 35M to 82M
- Hardware
- from: Laptop
Text to speechRUGGUF2025–2026
Zyphra · USA
Speech synthesis with voice cloning and fine control over emotion, speed and pitch.
- Voice cloning
- Emotional voiceover
- Voicing videos
- Sizes
- about 1.6B
- Hardware
- from: Laptop
Text to speechRUGGUF2025–2026
Resemble AI · USA
Speech synthesis with voice cloning and adjustable expressiveness. The multilingual version supports 23 languages, including Russian; Turbo and Flash are sped up for live dialogue.
- Voice for a bot or assistant
- Cloning a brand voice
- Voicing videos
- Sizes
- about 350M – 500M
- Hardware
- from: Laptop
Biology and chemistry2022–2026
EvolutionaryScale / Chan Zuckerberg Biohub (ESM-2 — Meta AI) · USA
Protein language models: they understand amino acid sequences, predict structure (ESMFold2) and help with protein design. Since 2026 all open versions are under MIT.
- Protein embeddings for predicting properties (stability, solubility)
- Predicting 3D structures of proteins and complexes
- Screening enzyme and antibody design candidates before lab work
- Sizes
- 8M – 15B (ESM-2), 300M – 6B (ESM C), 1.4B (open ESM3)
- Hardware
- from: Laptop
Image generationGGUF2025–2026
HiDream.ai · China
Open MIT-licensed image models: generation (I1), instruction-based editing (E1) and the unified O1-Image model that does both.
- Image generation from descriptions
- Editing images with words
- Variations of product photos
- Sizes
- about 9B – 17B
- Hardware
- from: 1 GPU
Image + textGGUF2025–2026
Kuaishou · China
Vision models from Kuaishou focused on short videos. Keye-VL-2.0 (30B, 3B active) understands well what happens in a clip and when.
- Analysing and describing short videos
- Reviewing clips and content
- Finding the right moment in a video
- Sizes
- 8B – 671B-A37B
- Hardware
- from: Laptop
Image + textOllama2023–2026
LLaVA / LMMs-Lab (researchers from the USA and China) · USA / China
The open project that started the trend for image-plus-text models. The OneVision line understands photos, documents and video; training data and recipes are open.
- Answering questions about photos and screenshots
- Describing products from a photo
- Frame-by-frame video analysis
- Sizes
- 0.5B – 72B
- Hardware
- from: Laptop
AvatarsGGUF2025–2026
Meituan · China
Audio-driven talking people built on LongCat-Video. Version 1.5 is production-ready: stable long videos in Chinese and English.
- News or course presenter videos
- Promo videos with a talking character
- Singing and voice-over
- Sizes
- based on LongCat-Video 13.6B
- Hardware
- from: 1 GPU
Documents and OCRGGUF2025–2026
Shanghai AI Laboratory (OpenDataLab) · China
A popular open tool for converting PDFs to Markdown with its own small model. MinerU2.5-Pro was improved through data alone, without growing in size. Languages on the card: Chinese and English.
- Converting PDF reports and contracts to Markdown
- Recognising tables and formulas
- Preparing documents for RAG and search
- Sizes
- 0.9B – 1.2B
- Hardware
- from: Laptop
Robotics2025–2026
Ai2 (Allen Institute for AI) · USA
A fully open robot control model that first "reasons" about space and trajectory, then acts. Its reasoning can be checked.
- Controlling a robot arm with explainable steps
- Fine-tuning for your own robot
- Research pilots
- Sizes
- 5B – 8B
- Hardware
- from: 1 GPU
Text to speechRU2025–2026
OpenMOSS (Fudan University) · China
A speech synthesis family: multi-voice dialogue voicing (TTSD), fast synthesis for live conversation and the tiny Nano. Version 1.5 supports 30+ languages, including Russian.
- Voicing podcasts and dialogues
- Voice for an assistant
- Voice cloning
- Sizes
- 100M – 8.5B
- Hardware
- from: Laptop
Documents and OCRRUGGUF2025–2026
Baidu (PaddlePaddle) · China
A compact document parsing model from the popular PaddleOCR toolkit. Per the model card it supports 109 languages, including Russian; version 1.6 leads the OmniDocBench benchmark.
- Recognising invoices, contracts and delivery notes, including in Russian
- Recognising tables, formulas and stamps
- Converting scans to Markdown and JSON
- Sizes
- 0.9B
- Hardware
- from: Laptop
Forecasting2024–2026
THUML, Tsinghua University · China
A compact forecasting foundation model from the Tsinghua lab: trained on a large set of diverse series and fine-tunable on your own data.
- Forecasting demand and load
- Forecasting sensor readings on the shop floor
- Fine-tuning forecasts on your own history
- Sizes
- 84M (timer-base)
- Hardware
- from: Laptop
3D2024–2026
VAST (TripoSR together with Stability AI) · China
VAST family: a 3D model from a single photo. TripoSR runs in under a second, TripoSG gives cleaner geometry, TripoSplat builds a scene from Gaussian points.
- 3D product model from a photo
- Object assets for games and AR
- Quick 3D prototype for printing
- Sizes
- up to 1.5B
- Hardware
- from: Laptop
Drawings and CADGGUF2026
Autodesk Research · USA
A model from Autodesk Research: from eight rendered views of a part it writes an executable CadQuery program. It was trained on synthetic data only. It produces a draft; an engineer checks and signs off the document.
- Getting a parametric model from a set of views of a part
- Converting finished geometry into editable code
- A draft model for a design office
- Sizes
- 2B (based on Qwen3-VL-2B)
- Hardware
- from: Laptop
TextGGUF2025–2026
ServiceNow · USA
ServiceNow 15B models with step-by-step reasoning that fit on a single GPU. From version 1.5 they also understand images and are good at calling tools.
- A reasoning assistant for internal services
- Tool calling and enterprise agents
- Analysing screenshots and documents with images
- Sizes
- 5B – 15B
- Hardware
- from: Laptop
TextRUGGUF2025–2026
Arcee AI · USA
An American family of MoE models trained from scratch: Nano, Mini and Large. Trinity-Large-Thinking (398B) reasons before answering.
- Agents with tool calling
- Reasoning tasks
- Corporate assistant on your own servers
- Sizes
- 6B – 398B-A13B
- Hardware
- from: Laptop
TextGGUF2025–2026
Baidu · China
Baidu's first open line: from a tiny 0.3B to MoE with 424 billion parameters, including versions that understand images. The mid-size 21B-A3B fits on one GPU; ERNIE-Image 8B draws images with text.
- Corporate assistant
- Analysis of documents and images
- Customer request classification
- Sizes
- 0.3B – 424B-A47B
- Hardware
- from: Laptop
Search and RAGRUOllama2024–2026
IBM · USA
Lightweight IBM embeddings for enterprise search, trained on data with clear rights. R2, released in 2026, became multilingual.
- Search across corporate documents
- RAG on a regular server without a GPU
- Reranking results
- Sizes
- 30M – 311M
- Hardware
- from: Laptop
Moderation and safetyOllama2024–2026
IBM · USA
IBM judge models: they catch harm, profanity and jailbreak attempts, and in RAG and agents check whether an answer is grounded in the documents. You can state your own rule in words.
- Checking bot requests and replies
- Finding made-up facts in knowledge-base answers
- Checking your own rules written as text
- Sizes
- 38M – 8B
- Hardware
- from: Laptop
Image + textOllama2025–2026
IBM · USA
Compact IBM models for business documents: tables, charts, forms, field-value pairs. The model card openly warns that it works best with English.
- Extracting fields from forms and invoices
- Turning charts and tables into data
- Answering questions about documents
- Sizes
- 2B – 4B
- Hardware
- from: Laptop
Avatars2024–2026
Fudan University · China
A series of audio-driven talking portraits: from short clips to hour-long 4K videos. Hallo-Live is built for real-time use.
- Presenter video from a photo and audio
- Long training videos
- Live avatar
- Sizes
- about 1B – 5B
- Hardware
- from: 1 GPU
Text to speech2025–2026
Kyutai · France
Streaming speech recognition and synthesis models from the makers of Moshi: they start speaking and transcribing without waiting for the end of a phrase. Pocket TTS (100M) runs on a CPU. English, French and a few other European languages, no Russian.
- Streaming speech transcription for voice bots
- Voicing replies with minimal delay
- Speech synthesis on a server without a GPU (Pocket TTS)
- Sizes
- 100M (Pocket TTS) – 2.6B
- Hardware
- from: Laptop
TextRU2024–2026
Ivan Bondarenko (bond005), Novosibirsk State University · Russia
Russian-language models for working with documents rather than chatting: knowledge-base answers, extraction of entities and facts from Russian text, long context.
- Answers to questions based on internal documents
- Extracting names, dates and amounts from contracts
- Short summaries of long Russian texts
- Sizes
- 1.5B – 7.6B
- Hardware
- from: Laptop
Text analysisOllama2024–2026
NuMind · France
Models for template-based data extraction: give it a document or scan and a JSON field template, get a filled-in JSON back. NuExtract3 (4B) also converts scans to Markdown.
- Extracting company details, amounts and dates from invoices and contracts into JSON
- Parsing receipts, waybills and forms against a set template
- Converting scans to Markdown for search
- Sizes
- 0.5B – 8B
- Hardware
- from: Laptop
Search and RAGGGUF2025–2026
Octen · USA / Singapore
Qwen3-Embedding models fine-tuned by the startup Octen for search in legal, financial and medical texts. As of January 2026 the 8B version topped the RTEB leaderboard.
- Search across contracts and case law
- Search across financial reports
- Search across long documents up to 32K tokens
- Sizes
- 0.6B – 8B
- Hardware
- from: Laptop
Moderation and safety2026
OpenAI · USA
Finds and hides personal data: names, addresses, phone numbers, emails, account numbers, passwords. Runs even in the browser. Trained mostly on English.
- Removing personal data from text before sending it to cloud AI
- Finding passwords and keys in texts
- Anonymizing correspondence for analytics
- Sizes
- 1.5B (50M active)
- Hardware
- from: Laptop
TranslationRU2020–2026
Helsinki-NLP, University of Helsinki · Finland
More than a thousand small translators, each for its own language pair. Russian-English and back are available. Fast even on a regular CPU.
- Bulk translation of short texts
- Translation right on the server without a GPU
- Translating reviews and requests before analysis
- Sizes
- 25M – 240M
- Hardware
- from: Laptop
Fact-checking and judgesRU2025–2026
SberDevices (ai-forever) · Russia
Judge models that evaluate other AI models' answers in Russian: they score against a given criterion and explain the score in text.
- Automatic quality checks of Russian chatbot answers
- Comparing several models before choosing one
- Checking answers after fine-tuning
- Sizes
- 4B – 32B
- Hardware
- from: Laptop
CodeOllama2025–2026
Essential AI · USA
An 8B model trained from scratch by the company of one of the authors of the transformer architecture. Strong at code and technical tasks; version 1.5 handles context up to 160K tokens.
- Writing and fixing code
- A developer agent on a single GPU
- Solving technical and scientific problems
- Sizes
- 8B
- Hardware
- from: Laptop
ForecastingGGUF2025–2026
Datadog · USA
A Datadog forecasting model trained on server and application metrics. Especially strong for IT monitoring: load, latency, errors.
- Server load forecasting
- Anomaly detection in metrics
- Capacity planning
- Sizes
- 4M – 2.5B
- Hardware
- from: Laptop
Text to speechRUGGUF2025–2026
OpenBMB (ModelBest, Tsinghua University) · China
Speech synthesis with voice cloning and natural intonation. VoxCPM2 supports 30 languages, including Russian.
- Voice cloning
- Voicing videos and audiobooks
- Voice for an assistant
- Sizes
- 0.5B – 2.3B
- Hardware
- from: Laptop
Acoustic monitoring2023–2026
Xiaomi · China
Compact sound-labelling models from 5.5M to 86M, with ONNX and INT8 builds that run on an ordinary CPU and on a board next to the equipment. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- Labelling sound on modest hardware and on site
- Detecting alarm sounds and abnormal noise
- Fine-tuning for your own set of equipment sounds
- Sizes
- 5.5M - 86M
- Hardware
- from: Laptop
Acoustic monitoring2024–2026
Xiaomi · China
A general-purpose audio encoder trained on 272 thousand hours of speech, music and noise: it gives features on top of which you train your own classifier of abnormal sounds. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- Audio features for your own anomaly model
- Finding similar fragments in a recording archive
- Fine-tuning for the sounds of one production line
- Sizes
- 86M - 1.2B
- Hardware
- from: Laptop
Avatars2026
SII-GAIR and Sand.ai · China
Generates video of a talking person with sound in one go: a single transformer processes text, video and audio. Speech in 7 languages; Russian is not among them. Fast distilled versions are available.
- Presenter video from a script
- Ad videos with a talking character
- Training videos with a narrator
- Sizes
- 15B
- Hardware
- from: 1 GPU
Documents and OCRRUGGUF2025–2026
rednote hilab (Xiaohongshu) · China
A multilingual document parsing model: text, tables, formulas and reading order in one pass. dots.mocr also turns charts and diagrams into vector SVG.
- Recognising invoices, contracts and delivery notes
- Converting tables into an editable format
- Converting charts and diagrams into vector format
- Sizes
- about 3B
- Hardware
- from: Laptop
Plates and vehicles2024–2026
ankandrew (open project) · not disclosed
A ready pipeline for plate recognition: plate detector and character reading in one package, with your own models pluggable. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Getting plate recognition running quickly on site
- Automatic vehicle access by list
- Logging vehicle entry and exit
- Sizes
- a lightweight plate detector paired with XS and S reading models
- Hardware
- from: Laptop
Plates and vehicles2024–2026
ankandrew (open project) · not disclosed
Lightweight models that read characters from an already cropped license plate and run on an ordinary CPU. Filming vehicles and people and storing such records is personal data processing: agree the procedure and retention with a lawyer.
- Reading a plate at entry and exit
- Matching a plate against a whitelist of passes
- Going through archived camera footage
- Sizes
- XS and S models on the CCT architecture
- Hardware
- from: Laptop
Voice: speakers and soundRU2026
FireRedTeam (Xiaohongshu) · China
A speech and sound event detector: tells apart speech, singing and music. In a 102-language test (the FLEURS set, which includes Russian) it beat Silero VAD and TEN VAD. Has a streaming mode.
- Cutting recordings before speech recognition
- Separating speech from music and singing in broadcasts and videos
- Speech detection in voice bots
- Sizes
- compact, exact size not stated
- Hardware
- from: Laptop
Math and reasoningGGUF2025–2026
Princeton University · USA
Open models for formal proofs in Lean 4 from Princeton. The new Goedel-Code-Prover proves program correctness.
- Formal verification of mathematical workings
- Verifying code correctness
- Training
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
Search and RAGRU2026
Microsoft · USA
Microsoft's 2026 multilingual embeddings with context up to 32K tokens; Russian is on the language list. The 270M and 0.6B versions run on a regular server, 27B is the most accurate.
- Multilingual knowledge base search
- Picking passages for RAG
- Search across long documents
- Sizes
- 270M – 27B
- Hardware
- from: Laptop
MedicineGGUF2025–2026
Zhejiang University · China
A medical model for text, images, 3D scans and video: from a light 4B to a large MoE. Does not replace a doctor; decisions are made by a specialist.
- Hints for doctors when reviewing images and CT scans
- Draft reports and discharge summaries
- Searching medical literature
- Sizes
- 4B – 235B-A22B
- Hardware
- from: Laptop
Image + textRUGGUF2023–2026
Shanghai AI Laboratory (OpenGVLab) · China
A large family of Chinese vision models sized from 1B to 241B. InternVL-U (4B) combines image understanding, generation and editing.
- Understanding documents, diagrams and charts
- Answering questions about photos
- Video analysis
- Sizes
- 1B – 241B-A28B
- Hardware
- from: Laptop
Video2025–2026
Skywork AI (Kunlun) · China
An interactive "world model": generates video of a game world in real time and responds to keyboard and mouse input. Version 3.0 keeps scene memory for minutes.
- Game world prototypes without an engine
- Interactive demos and simulations
- Generating data to train agents
- Sizes
- 1.8B – 17B
- Hardware
- from: 1 GPU
Image + text2024–2026
Ai2 (Allen Institute for AI) · USA
Fully open vision models from Ai2 (weights and data). They can point to a spot in an image and count objects; Molmo2 understands video, MolmoWeb controls a browser.
- Counting products and objects in photos
- Pointing to where an item is in an image
- Video analysis
- Sizes
- 1B-A7B – 72B
- Hardware
- from: Laptop
Drawings and CADGGUF2025–2026
Fudan University and StepFun · China
A family of models that produce SVG both from an image and from a text description, from a simple icon to a detailed illustration. For precise drawings the result has to be checked against the original.
- Vectorising images and symbols into SVG
- Creating icons and pictograms from a text description
- Preparing vector graphics for web and print
- Sizes
- 3B – 8B
- Hardware
- from: 1 GPU
Tabular data2025–2026
Lexsi Labs · India
Recent open models for tabular data: they predict from a few examples given in the prompt, with no task-specific training.
- Classification and forecasting on tables with no separate training
- Quickly testing models on new datasets
- Assessing features in large tables
- Sizes
- size not stated on the model card
- Hardware
- from: Laptop
Plates and vehicles2022–2026
PaddlePaddle (Baidu) · China
A ready set of models for vehicle tasks: plate recognition, car color and type, counting entries and exits, spotting parking where it is not allowed. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Counting traffic flow
- Identifying car type and color
- Reading the plate at the entrance
- Sizes
- a set of models: vehicle detector, attributes, plate reading on PP-OCR
- Hardware
- from: Laptop
Documents and OCRRUGGUF2026
Baidu (Qianfan) · China
A Baidu model that not only recognises a document but also answers questions about it. Per the model card it supports 192 languages, including Cyrillic.
- Recognising invoices, contracts and delivery notes, including in Russian
- Page layout analysis and table recognition
- Answering questions about a document
- Sizes
- 4B
- Hardware
- from: Laptop
Music and sound2025–2026
Alibaba Tongyi (FunAudioLLM) · China
Generates and edits audio for video, text or audio, first "reasoning" about the scene with a multimodal model. PrismAudio is the next version for video-to-audio.
- Audio for video based on the scene
- Editing individual sounds in a track
- Sound effects from a description
- Sizes
- size not stated on the model card
- Hardware
- from: 1 GPU
Biology and chemistry2024–2026
Arc Institute (with Together AI, Stanford, NVIDIA) · USA
DNA language models with context up to a million nucleotides: they assess the impact of mutations, annotate genomes and generate sequences. Evo 2 is trained on genomes from all domains of life.
- Assessing the likely harmfulness of genetic variants for research
- Annotating genomes of microorganisms and plants
- Finding promising sequences in breeding and synthetic biology
- Sizes
- 1B – 40B
- Hardware
- from: 1 GPU
Plates and vehicles2026
Autolane · not disclosed
A recent set of plate recognition weights: two plate detectors and a reading model, trained on US plates, so the Russian format needs fine-tuning. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Finding the plate in a frame
- Reading the plate characters
- Running on cameras and single-board computers
- Sizes
- RF-DETR and YOLOX-S detectors, CCT-S for character reading
- Hardware
- from: Laptop
Virtual try-on2026
FASHN AI · Israel
A rare open try-on model with a commercial license: mask-free, accepts a photo of the item on a model or a flat lay. Weights are about 2 GB.
- Product cards on a model without a photo shoot
- Fitting room on a store website
- Catalog from flat-lay clothing photos
- Sizes
- 972M
- Hardware
- from: 1 GPU
Computer-use agents2025–2026
Alibaba (Tongyi Lab, X-PLUG) · China
Models for controlling phones and computers from the Mobile-Agent project: they work with Android, Windows, macOS and the browser; version 1.5 has a reasoning mode.
- Automating actions in mobile apps
- Working in desktop software without an API
- Testing apps against scenarios
- Sizes
- 2B – 32B
- Hardware
- from: Laptop
Image generationGGUF2025–2026
Meituan · China
Meituan's 6B image generation and editing model. Renders Chinese text well; has a fast version for edits.
- Image generation from descriptions
- Instruction-based photo editing
- Visuals for product cards
- Sizes
- 6B
- Hardware
- from: 1 GPU
Voice assistantsGGUF2025–2026
OpenBMB (ModelBest, Tsinghua University) · China
A small model that sees, hears and replies by voice in real time, and can clone a voice. Voice dialogue in English and Chinese, text in 30+ languages.
- Voice assistant on your own server
- Analyzing videos and documents
- Voice answers about a camera image
- Sizes
- 8B – 9B
- Hardware
- from: Laptop
Math and reasoningGGUF2026
LM Provers (CMU, Hugging Face, ETH Zurich, Project Numina) · USA, Switzerland, France
A small 4B model on Qwen3 that writes mathematical proofs in plain language almost at the level of large models. Runs on a laptop.
- Checking the logic of reasoning and workings
- Step-by-step explanations of solutions
- Training and olympiad preparation
- Sizes
- 4B
- Hardware
- from: Laptop
CodeOllama2024–2026
Alibaba (Qwen team) · China
The broadest open coding family: from 0.5B for autocompletion to 480B for agents. Qwen3-Coder-Next (80B, 3B active) works as a developer agent on a single GPU.
- Code autocompletion in the editor
- An agent that edits code in the repository on its own
- Writing and refining scripts, SQL and integrations
- Sizes
- 0.5B – 480B-A35B
- Hardware
- from: Laptop
Image + text2026
Sukhrob Nurali · not disclosed
A fine-tuned Qwen3-VL-8B reads resume pages as images and returns a 23-field JSON record. The author states plainly that the model is not meant for automated decisions about candidates; a human decides.
- Moving a resume from PDF into a candidate record
- Filling a candidate database without manual typing
- Parsing resumes with different layouts and styling
- Sizes
- 8B, a fine-tune of Qwen3-VL-8B-Instruct
- Hardware
- from: 1 GPU
Code2026
Ai2 (Allen Institute for AI) · USA
Fully open developer agents from Ai2: weights, data and training recipe are all public. Designed so a company can cheaply fine-tune the agent on its own repository.
- An agent for fixing issues in code
- Fine-tuning the agent on an internal repository
- Automating small edits and tests
- Sizes
- 8B – 32B
- Hardware
- from: Laptop
Tabular data2025–2026
Inria (Soda team) · France
An open tabular model from the creators of scikit-learn: classifies and predicts from examples without training and handles tables of up to hundreds of thousands of rows. The license allows business use.
- Predicting customer churn
- Scoring applications and deals
- Classifying customers from 1C and CRM data
- Sizes
- about 25–30M
- Hardware
- from: Laptop
MedicineGGUF2025–2026
Ant Healthcare (Ant Group) and Zhejiang Provincial Medical Information Center · China
A large medical MoE model based on Ling-flash-2.0: 100B parameters with 6B active, so it answers quickly. Does not replace a doctor; decisions are made by a specialist.
- Reference answers to staff on clinical questions
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Sizes
- 100B-A6B
- Hardware
- from: 1 GPU
Documents and OCROllama2025–2026
DeepSeek · China
An OCR model that compresses a page into a small number of visual tokens, so it processes large volumes quickly. Version 2 better understands reading order.
- Bulk recognition of scanned invoices and contracts
- Table recognition
- Converting PDFs to Markdown for search and RAG
- Sizes
- about 3B
- Hardware
- from: Laptop
Avatars2024–2026
Ant Group · China
Ant Group's talking avatars: the face and, from V2, hand gestures. V3-Flash produces video in 8 steps and fits into 12 GB of GPU memory.
- Presenter video from a photo and voice
- Avatar with gestures for presentations
- Voiced characters
- Sizes
- up to 1.3B
- Hardware
- from: 1 GPU
Weather and climate2024–2026
European Centre for Medium-Range Weather Forecasts (ECMWF) · Europe (intergovernmental organization)
ECMWF's weather neural network running operationally: a 15-day forecast four times a day, an ensemble version with 51 scenarios, and since version 2, ocean waves.
- Running your own forecast from open initial data
- Ensemble forecasts to estimate the probability of frost, downpours and storms
- Wave forecasts for marine operations
- Sizes
- checkpoint of about 1 GB
- Hardware
- from: 1 GPU
TextRUGGUF2024–2026
UTTER consortium (Unbabel, universities of Lisbon, Edinburgh, Amsterdam and others) · European Union
European language models trained on all EU languages and several others, with a focus on translation. Russian is supported. Permissive license.
- Translation and localization of texts
- Answering questions in different languages
- Draft emails for foreign partners
- Sizes
- 1.7B – 22B
- Hardware
- from: Laptop
Computer-use agentsGGUF2026
Meituan · China
Meituan's computer-control agent, trained on a large number of simulated tasks in desktop software. It outputs clicks and keyboard input.
- Working in office and legacy software without an API
- Moving data between systems
- Running test scenarios
- Sizes
- 8B – 32B
- Hardware
- from: 1 GPU
Image generation2026
Zhipu AI (Z.ai) · China
A hybrid of a 9B language model and a 7B decoder. Strong at text-heavy images: posters, infographics, slides.
- Posters and banners with text
- Infographics
- Illustrations for presentations
- Sizes
- 9B + 7B
- Hardware
- from: 1 GPU
Documents and OCRRUOllama2026
Zhipu AI (Z.ai) · China
A lightweight OCR model from Zhipu for document parsing. The model card lists Russian among supported languages; built for high load and low-end hardware.
- Recognising invoices, contracts and delivery notes, including in Russian
- Recognising tables and formulas
- Extracting fields to JSON
- Sizes
- 0.9B
- Hardware
- from: Laptop
TextGGUF2024–2026
Prime Intellect · USA
Models trained in a distributed way on GPUs from around the world. INTELLECT-3 (106B) is further trained with reinforcement learning for math, code and agents.
- Reasoning and math tasks
- Programming help
- Agents with tool calling
- Sizes
- 10B – 106B-A12B
- Hardware
- from: 1 GPU
MedicineGGUF2025–2026
Alibaba DAMO Academy · China
Alibaba's medical model based on Qwen2.5-VL: understands many types of medical images and medical text, and can reason step by step. Does not replace a doctor; decisions are made by a specialist.
- Hints for doctors when reviewing images
- Draft reports and discharge summaries
- Searching medical literature
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
AvatarsGGUF2025–2026
Alibaba (Quark) · China
A real-time streaming avatar of unlimited length. Suits live broadcasts and dialogue, but needs powerful server hardware.
- Live avatar for customer dialogue
- Endless broadcasts with a presenter
- Interactive characters
- Sizes
- 14B
- Hardware
- from: 1 GPU
VideoGGUF2026
OpenMOSS / MOSI · China
Generates video with sound in one pass: lip-synced speech, effects and ambience. A 32B-parameter MoE architecture, with 360p and 720p versions.
- Short clips with speech and sound from a description
- Ad scenes with dialogue
- Video prototypes for storyboards
- Sizes
- 32B-A18B
- Hardware
- from: 1 GPU
TextOllama2024–2026
Allen Institute for AI (Ai2) · USA
Fully open models: not only the weights but also the data, training code and intermediate checkpoints are published. Useful when transparent provenance matters.
- Assistant and answers based on documents
- Reasoning tasks (Think versions)
- Fine-tuning on your data with a clear model history
- Sizes
- 1B – 32B
- Hardware
- from: Laptop
TextRUOllama2023–2026
Microsoft · USA
Small Microsoft models trained on carefully selected data: strong at logic and math for their modest size. Versions with images and speech are available.
- Assistant on a laptop or your own server
- Reasoning and calculation tasks
- Analysis of images and diagrams (vision versions)
- Sizes
- 1.3B – 42B-A6.6B
- Hardware
- from: Laptop
Search and RAGRUOllama2025–2026
Alibaba (Qwen) · China
Embeddings and rerankers based on Qwen3, among the best open ones for multilingual search, including Russian. VL versions search images, screenshots and video.
- Knowledge base search for RAG
- Reranking results before answering
- Search across scans, slides and screenshots
- Sizes
- 0.6B – 8B
- Hardware
- from: Laptop
Text to speechRUGGUF2026
Alibaba (Qwen) · China
Speech synthesis in 10 languages, including Russian: voice cloning from 3 seconds, ready-made voices and creating a voice from a text description.
- Voice for a bot or assistant
- Cloning a brand voice
- Choosing a voice by description
- Sizes
- 0.6B – 1.7B
- Hardware
- from: Laptop
Voice: speakers and soundRU2025–2026
Daily (Pipecat) · USA
Uses intonation to tell whether a person has finished a thought or just paused, so a voice bot does not interrupt. Version 3 is 8 MB, runs on a CPU and understands 23 languages, including Russian.
- Voice bot does not interrupt the customer during pauses
- Fast reply when the customer has really finished
- An add-on to a standard speech detector in voice assistants
- Sizes
- 8M (v3) – 580M (v1)
- Hardware
- from: Laptop
Search and RAG2026
Voyage AI (MongoDB) · USA
The only open model in the Voyage 4 line: its vectors are compatible with the paid larger versions, so you can start locally and move to the API later.
- Document search on your own server
- RAG for small knowledge bases
- Finding similar texts
- Sizes
- about 340M
- Hardware
- from: Laptop
Image generationGGUF2025–2026
Alibaba (Tongyi-MAI) · China
A compact 6B model with photorealism on par with large models. The Turbo version produces an image in a few steps on a regular gaming GPU.
- Photorealistic ad images
- Images with English and Chinese text
- Bulk visual generation
- Sizes
- 6B
- Hardware
- from: 1 GPU
Moderation and safety2025
ServiceNow · USA
A guard model that catches both harmful content and attacks on AI (prompt injection, jailbreaks), including when agents use tools.
- Screening chatbot requests for attacks and jailbreaks
- Filtering harmful model answers
- Monitoring the actions of AI agents that use tools
- Sizes
- 8B
- Hardware
- from: Laptop
Image + text2023–2025
Zhipu AI (Z.ai) and Tsinghua University · China
Vision models from Zhipu: first CogVLM, then the GLM-V line. GLM-4.6V can call tools based on images and act as an agent operating an interface.
- Answering questions about photos and documents
- An agent that operates an interface from screenshots
- Analysing charts and reports
- Sizes
- 9B – 106B-A12B
- Hardware
- from: Laptop
Text to speechRU2024–2025
Alibaba (Tongyi, FunAudioLLM) · China
Speech synthesis with voice cloning from a short sample and streaming output for live dialogue. Version 3 supports 9 languages, including Russian.
- Voice for a bot or assistant
- Cloning a brand voice
- Voicing videos
- Sizes
- 300M – 0.5B
- Hardware
- from: Laptop
TextGGUF2023–2025
Inception (G42), MBZUAI and Cerebras · UAE
A model family for Arabic and English, including Gulf dialects. Suits companies working with Arabic-speaking customers and government bodies in the region.
- A chatbot in Arabic and English
- Translating and summarising documents in Arabic
- Classifying customer requests
- Sizes
- 256M – 70B
- Hardware
- from: Laptop
Computer-use agentsGGUF2025
Alibaba (Tongyi-MAI) · China
Compact Alibaba models for working in smartphone and computer interfaces: they find elements and complete multi-step tasks. The agent acts on the user's behalf inside their apps, so access rights and limits are set before launch. The follow-up line, Qwen-UI-Agent, was announced in July 2026, but its weights have not been released.
- Automating actions in mobile apps
- Working in software without an API
- UI autotests
- Sizes
- 2B – 8B
- Hardware
- from: Laptop
3D2025
Meta and Carnegie Mellon University · USA
A single model builds a metric 3D reconstruction from photos, and uses camera, depth or pose data when available. One weights variant is under Apache 2.0.
- 3D reconstruction of an object or room from photos
- Exporting the scene to COLMAP format for further processing
- Depth and camera pose estimation
- Sizes
- about 1.2B
- Hardware
- from: 1 GPU
Speech to textRU2025
Meta · USA
Speech recognition for 1,600+ languages, including Russian and rare languages no system supported before. A new language can be added from a few examples.
- Transcription in rare and local languages
- Digitizing oral archives
- Subtitles in many languages
- Sizes
- 300M – 7B
- Hardware
- from: Laptop
Computer vision2025
Meta · USA
Meta's family of encoders for images and video, and with PE-AV also for audio. PE-Core searches by text more accurately than SigLIP 2 (per Meta); small versions are available.
- Search photos and videos by description
- Catalog labeling and tagging
- Search across audio and video (PE-AV)
- Sizes
- size not stated on the model card
- Hardware
- from: Laptop
Tabular dataGGUF2024–2025
Zhejiang University · China
A family for working with tables and databases: it understands data structure, writes parsing code and answers questions about exports.
- Answering questions about tables and data exports
- Automated data analysis with generated code
- A helper for BI and internal reporting
- Sizes
- 7B – 72B
- Hardware
- from: 1 GPU
3DGGUF2024–2025
Microsoft · USA
One of the strongest open 3D models: from an image or text it produces a textured mesh or a Gaussian scene. TRELLIS.2 is noticeably more detailed than the first version.
- 3D models of products and interiors from photos
- Assets for games and AR/VR
- Prototypes for 3D printing
- Sizes
- up to 4B (TRELLIS.2)
- Hardware
- from: 1 GPU
Deepfake detection2024–2025
Meta · USA
A watermark for video and images that survives re-encoding and cropping. The detector errs in both directions: a missing mark does not prove a forgery, and finding one is a reason for a human to check.
- Marking video created or processed by AI
- Finding your own mark in re-uploaded clips
- Protecting ad materials from being reused as someone else's
- Sizes
- a mark of 96 to 1024 bits
- Hardware
- from: Laptop
TextRUGGUF2024–2025
Vikhr Models · Russia
Russian-language fine-tunes of open models (Mistral, Qwen, Llama) by the independent Vikhr team, with compact versions for a regular PC. Borealis is an audio model for recognizing and understanding Russian speech.
- Russian-language assistant on your own PC or server
- Knowledge-base answers (RAG)
- Texts and emails in Russian
- Sizes
- 0.5B – 24B
- Hardware
- from: Laptop
Text to speech2025
Nari Labs · South Korea
A model that voices entire two-person dialogues with laughter, sighs and pauses. English only.
- Voicing dialogues and podcasts
- Ads with natural speech
- Training role-plays
- Sizes
- 1B – 2B
- Hardware
- from: Laptop
Satellite and geo2025
IBM and the European Space Agency (ESA) · USA / Europe
A multimodal Earth model: understands optical and radar imagery, terrain, vegetation index and land use maps, and can generate a missing data type (for example, a "see-through-clouds" image from radar).
- Analyzing fields and forests even in cloudy weather using radar imagery
- Land use maps for assessing plots
- Flood and wildfire assessment (ready-made fine-tunes available)
- Sizes
- tiny – large (checkpoints from ~200 MB to ~3.8 GB)
- Hardware
- from: Laptop
Acoustic monitoring2025
Carnegie Mellon University and co-authors (the ESPnet project) · USA
A fully open reproduction of BEATs: code, training recipes and weights are all published. Teams pick it when they need a transparent base for their own sound model. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- A transparent base for your own audio model
- Fine-tuning on your own equipment recordings
- Labelling sound events
- Sizes
- base and large versions, exact sizes are listed on the model cards
- Hardware
- from: Laptop
Video2025
Character.AI · USA
Generates video together with sound and speech from text or an image: two branches (video based on Wan 2.2 and a 5B audio branch) run in sync. Needs 24–32 GB of GPU memory.
- Short clips with talking characters
- Animating an image with voice-over
- Ad scene prototypes
- Sizes
- 11B
- Hardware
- from: 1 GPU
Drawings and CAD2025
Kingsoft · China
It reads a flowchart from an image and first writes out its structure as JSON - blocks, links and branching conditions - and only then answers a question about the chart. The parse still has to be checked against the original.
- Converting a flowchart image into a JSON structure
- Answering questions about a process diagram
- Digitising procedures and diagrams from presentations
- Sizes
- 32B
- Hardware
- from: 1 GPU
Voice: speakers and soundRU2020–2025
Silero · Russia
The most popular open speech detector: tells voice apart from silence and noise. Processes an audio chunk in under a millisecond on a single CPU core; trained on recordings in more than 6,000 languages.
- Cutting calls and recordings before speech recognition
- Detecting when the customer is speaking in a voice bot
- Filtering out silence and noise to save on transcription
- Sizes
- about 2 MB
- Hardware
- from: Laptop
Rerankers2025
ZeroEntropy · USA
Rerankers built on Qwen3. The model card lists the target domains — finance, law, code, medicine, science; the stated language is English.
- Refining results before an AI assistant answers
- Sorting search results across contracts and reports
- Search across technical and scientific documentation
- Sizes
- zerank-2 — 4B (based on Qwen3-4B), plus a smaller "small" version
- Hardware
- from: Laptop
TextRU2025
Avito Tech · Russia
Avito's model based on Qwen3-8B, retrained for Russian: its own tokenizer encodes Russian text more efficiently. Supports function calling.
- Product and listing descriptions in Russian
- Chatbot that calls internal services
- Request analysis and classification
- Sizes
- 7.9B
- Hardware
- from: Laptop
Image + textRU2025
Avito Tech · Russia
Avito's Russian-language model that understands images: describes photos, answers questions about an image, reads text on it. Based on Qwen2.5-VL, faster in Russian than the original.
- Product descriptions from photos in Russian
- Checking that a photo matches its description
- Reading brands and text in images
- Sizes
- 7.4B
- Hardware
- from: 1 GPU
Biology and chemistry2024–2025
MIT (Jameel Clinic) and Recursion · USA
An open MIT-licensed alternative to AlphaFold 3: predicts structures of protein, DNA and small-molecule complexes; Boltz-2 estimates binding strength, BoltzGen designs new binding proteins.
- Predicting how a candidate molecule binds to a target protein
- Ranking compounds by predicted binding strength before synthesis
- Designing binder proteins for a given target
- Sizes
- checkpoints of about 2 GB
- Hardware
- from: 1 GPU
ForecastingGGUF2024–2025
Amazon · USA
Amazon forecasting models, among the most downloaded. Chronos-2 takes external factors into account: prices, promotions, weather.
- Demand forecasting with promotions and prices
- Inventory planning
- Forecasting revenue and customer flow
- Sizes
- 8M – 710M
- Hardware
- from: Laptop
Music and sound2025
ASLP-lab (Northwestern Polytechnical University) · China
Fast generation of a full song with vocals from lyrics and a style sample, up to several minutes long.
- Songs and jingles from lyrics
- Music for videos
- Demo versions of tracks
- Sizes
- about 1.1B
- Hardware
- from: Laptop
Moderation and safetyOllama2025
OpenAI · USA
Moderation by your own rules: you write the policy in plain text, and the model reasons and gives a decision with an explanation. Built on gpt-oss.
- Moderation by internal company rules
- Labeling disputed messages with an explanation
- Checking reviews and listings before publishing
- Sizes
- 20B – 120B
- Hardware
- from: 1 GPU
VideoGGUF2025
Meituan · China
A 13.6B video model: from text, from an image and video continuation. Keeps quality on clips several minutes long.
- Long videos
- Video from a photo
- Continuing an existing video
- Sizes
- 13.6B
- Hardware
- from: 1 GPU
Recommenders2025
MiniOneRec open project · China
A small open generative recommender at 1.5B with published checkpoints and a full training pipeline. Handy as a learning and starter option; a real store needs fine-tuning on its own orders.
- A quick recommendation prototype on your own data
- Testing ideas before running a large model
- Training a team to work with generative recommendations
- Sizes
- 1.5B
- Hardware
- from: Laptop
Visual document search2025
Illuin Technology, EPFL, CentraleSupélec · France
A compact (250M) model for searching document pages as images. According to the authors, it matches models 10 times larger and runs without a GPU.
- Search across scans and PDFs on a modest server
- Indexing document archives
- Search across slides and manuals
- Sizes
- 250M
- Hardware
- from: Laptop
Search and RAGRUOllama2024–2025
Mixedbread · Germany
Embeddings and rerankers from Germany's Mixedbread. mxbai-embed-large is one of the most downloaded English search models; the v2 rerankers cover 100+ languages, including Russian.
- Search across a knowledge base
- Reranking results before a bot answers
- Product catalog search
- Sizes
- 17M – 1.5B
- Hardware
- from: Laptop
Documents and OCRGGUF2025
Ai2 (Allen Institute for AI) · USA
A model and toolkit for converting PDFs into clean text at scale, preserving reading order, tables and formulas. Built to process millions of pages.
- Bulk digitisation of a PDF archive
- Converting contracts and reports into text
- Preparing documents for search and RAG
- Sizes
- 7B
- Hardware
- from: 1 GPU
Image + textRUOllama2023–2025
Alibaba (Qwen team) · China
One of the strongest open vision models: reads documents, tables, charts and video, and works with user interfaces. Since Qwen3.5, vision is built directly into the main Qwen model.
- Extracting data from scanned invoices and delivery notes
- Analysing photos of products and shelves
- Analysing video and camera footage
- Sizes
- 2B – 235B-A22B
- Hardware
- from: Laptop
Search and RAGOllama2023–2025
BAAI (Beijing Academy of Artificial Intelligence) · China
Some of the most popular embeddings for search and RAG. The main v1.5 versions target English and Chinese; for Russian, BAAI has a separate model, bge-m3.
- Search across English-language documents
- Picking passages for chatbot answers (RAG)
- Code search (bge-code)
- Sizes
- 24M – 9B
- Hardware
- from: Laptop
Satellite and geo2023–2025
IBM and NASA · USA
Foundation models for Landsat and Sentinel-2 satellite imagery that account for image time series. Ready-made fine-tunes for floods, burn scars and crop types, plus a separate weather model, WxC.
- Mapping crops and field condition over the season
- Assessing flood zones and burn scars after natural disasters
- Monitoring changes in buildings and land use
- Sizes
- tiny – 600M (imagery), 2.3B (Prithvi WxC weather)
- Hardware
- from: Laptop
Text to SQLGGUF2024–2025
Prem AI · UK
A text-to-SQL model of just 1B parameters, designed to run locally so the database never leaves for external services.
- Local translation of questions into SQL with no internet access
- Query hints on modest hardware
- Embedding into internal analytics tools
- Sizes
- 1B
- Hardware
- from: Laptop
Voice: speakers and sound2022–2025
pyannoteAI (Hervé Bredin) · France
The most widely used open tool for splitting a recording by speaker: who spoke and when. Usually paired with speech recognition. Weights are issued after a short form on HF.
- Tagging calls: which part is the agent, which is the customer
- Meeting minutes with speaker labels
- Preparing recordings for transcription and analysis
- Sizes
- a few million parameters
- Hardware
- from: Laptop
Voice assistantsRUGGUF2025
Alibaba (Qwen) · China
Models that understand text, images, audio and video and reply by voice in real time. Qwen3-Omni speaks 10 languages, including Russian.
- Voice assistant for customers
- Analyzing calls and videos
- Voice answers about documents and images
- Sizes
- 3B – 30B-A3B
- Hardware
- from: Laptop
Moderation and safetyRUGGUF2025
Alibaba (Qwen) · China
Safety filters for 119 languages, Russian among them. The Stream version checks a bot's reply while it is being generated and can cut it off on the fly.
- Filtering bot requests in Russian
- Stopping a dangerous reply during generation
- Labeling messages by risk category
- Sizes
- 0.6B – 8B
- Hardware
- from: Laptop
Documents and OCR2025
IBM and Hugging Face · USA
Tiny models for the open Docling document converter: they turn a page into markup with tables, formulas and code. Run on an ordinary laptop.
- Converting PDFs and scans to Markdown for search and RAG
- Recognising tables in reports
- Processing invoices and contracts on an ordinary PC
- Sizes
- 256M – 258M
- Hardware
- from: Laptop
Speech to textRU2023–2025
Alpha Cephei · Russia
Offline Russian speech recognition that runs even on a Raspberry Pi or a phone, without internet. Streaming models for live audio and simple Russian speech synthesis, Vosk TTS, are available.
- Transcribing Russian calls and recordings without the cloud
- Voice control in apps and kiosks
- Low-latency streaming speech recognition
- Sizes
- about 45 MB – 1.8 GB
- Hardware
- from: Laptop
Voice: speakers and sound2024–2025
Alibaba (Tongyi Lab) · China
Alibaba's set of speech cleanup models: noise suppression, separating overlapping voices, upscaling audio to 48 kHz, and isolating a voice using video of the speaker's face.
- Noise suppression in conversation recordings
- Separating two voices speaking at once
- Improving old and phone recordings
- Sizes
- under 1B
- Hardware
- from: Laptop
TextOllama2025
OpenAI · USA
OpenAI's first open models since GPT-2. Reasoning and tool calling; the smaller version fits on a single GPU.
- AI agent that calls internal systems
- Answers based on internal policies
- Drafts of emails and reports
- Sizes
- 20B, 120B
- Hardware
- from: 1 GPU
Math and reasoningGGUF2025
Moonshot AI and Project Numina · China, France
Models for formal proofs in Lean 4 from Moonshot AI (Kimi) and Numina. Small versions from 0.6B run on a laptop.
- Formal verification of mathematical workings
- Translating a problem from plain language into Lean
- Training and olympiad preparation
- Sizes
- 0.6B – 72B
- Hardware
- from: Laptop
Text analysisRUGGUF2025
Johns Hopkins University (JHU CLSP) · USA
A multilingual encoder trained on more than 1800 languages. The list includes Tatar, Bashkir, Chuvash, Udmurt, Buryat, Komi, Ingush and other languages of Russia. A base for classifiers and search over such texts.
- Classifying requests and documents in national languages
- Semantic search over texts in rare languages
- Extracting names, dates and titles from text
- Sizes
- 140M and 307M
- Hardware
- from: Laptop
Avatars2025
Meituan · China
Dubbing and talking characters built on Wan: MultiTalk handles dialogue between several people, InfiniteTalk re-dubs videos of any length with facial and body motion.
- Video dubbing with matched facial expressions
- Dialogue between two characters from audio
- Long videos with a presenter
- Sizes
- 14B
- Hardware
- from: 1 GPU
Acoustic monitoring2025
Google DeepMind · USA
A model for acoustic monitoring of nature: it recognises about 15,000 species and provides features for your own tasks, and the license allows commercial use. A microphone on site also records people voices, which is personal data, so check the procedure with a lawyer.
- Monitoring the sound background of a site or water area
- Environmental audio features for your own model
- Selecting events from round-the-clock recordings
- Sizes
- size not stated on the model card
- Hardware
- from: Laptop
TextRU2024–2025
Lomonosov Moscow State University Research Computing Center, LAIR lab (RefalMachine) · Russia
Qwen models adapted for Russian: a new tokenizer plus further training on Russian texts. As a result, Russian text is generated up to twice as fast as with the original model of the same size.
- Russian-language assistant on your own server
- Answers based on company documents (RAG) in Russian
- Analysis and summaries of long Russian texts
- Sizes
- 1.5B – 32B
- Hardware
- from: Laptop
TextGGUF2025
ByteDance · China
An open ByteDance 36B model with up to 512K tokens of context and an adjustable thinking budget. Fits on a single powerful GPU.
- Analysis of long documents
- Agents with tools
- Corporate assistant
- Sizes
- 36B
- Hardware
- from: 1 GPU
Photo editingGGUF2024–2025
Nankai University · China
An open MIT-licensed model for precise object segmentation and background removal. RMBG-2.0 is built on it. Versions for 2K and for hair and semi-transparent edges.
- Bulk background removal from product photos
- Precise masks for design and print
- Cutting out people with hair for advertising
- Sizes
- about 220M (lightweight lite versions available)
- Hardware
- from: Laptop
Fact-checking and judges2024–2025
OpenCompass (Shanghai AI Laboratory) · China
A line of judges from the team behind open model benchmarks: they score answers and check them against a reference. The judge itself makes mistakes and does not replace manual review on important tasks.
- Scoring model answers against set criteria
- Checking an answer against a reference solution
- Comparing several models on your own data
- Sizes
- 1.5B – 32B
- Hardware
- from: Laptop
Math and reasoningOllama2025
Agentica (Berkeley, Sky Computing Lab) and Together AI · USA
Small models fine-tuned with reinforcement learning: DeepScaleR (1.5B) solves olympiad maths, DeepCoder writes code, DeepSWE works as a developer agent. Recipes and data are open.
- Solving maths problems with step-by-step working
- Generating and checking code
- An agent for fixing bugs in a repository
- Sizes
- 1.5B – 32B
- Hardware
- from: Laptop
MedicineGGUF2025
Intelligent Internet · UK
Reasoning medical models on Qwen3, designed to run on an ordinary computer. Does not replace a doctor; decisions are made by a specialist.
- Reference answers to staff with the reasoning shown
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
Finance2025
Tsinghua University (NeoQuasar) · China
A foundation model for market candlestick data: trained on data from more than 45 exchanges, it forecasts prices and volumes. The largest version, large, is not open.
- Forecasting candlesticks and trading volumes
- Volatility estimation
- A base for fine-tuning on your own series
- Sizes
- 4.1M – 102M
- Hardware
- from: Laptop
TranslationRUGGUF2025
ByteDance Seed · China
A compact ByteDance translator for 28 languages, close in quality to large closed systems. Russian is supported. Ready-made compressed versions are available.
- Translating business correspondence and documents
- Translating product cards
- Translating technical and legal texts
- Sizes
- 7B
- Hardware
- from: Laptop
TextRUOllama2024–2025
Hugging Face · USA
Tiny open Hugging Face models for phones and laptops. SmolLM3 (3B) can reason and handle long context; the full training recipe is open.
- Simple on-device assistant
- Classification and routing of requests
- Base for fine-tuning on a narrow task
- Sizes
- 135M – 3B
- Hardware
- from: Laptop
Speech to textRU2025
T-Bank · Russia
A compact T-Bank streaming model for recognizing Russian speech in phone calls. Works in real time even without a GPU.
- Transcribing phone calls
- Voice robots on the line
- Call quality control
- Sizes
- 72M
- Hardware
- from: Laptop
Deepfake detection2024–2025
Meta · USA
An image watermark that can be applied to individual regions: the model shows which part of the image is marked. It errs in both directions - a human reviews the result.
- Marking generated and edited images
- Finding a marked fragment inside a collage
- Tracking which parts of a picture were made by AI
- Sizes
- a mark encoder and decoder for images
- Hardware
- from: Laptop
Voice: speakers and sound2024–2025
RVC-Boss and community · China
Speech synthesis with voice cloning: a 5-second sample is enough, and after fine-tuning on a minute of recording the voice sounds noticeably more accurate. Use only with the voice owner's consent.
- Voicing texts with a specific narrator's voice
- Voice for a bot or assistant
- Dubbing training videos
- Sizes
- under 1B
- Hardware
- from: Laptop
Search and RAGGGUF2024–2025
TechWolf · Belgium
A model from a Belgian HR company: it turns job titles into vectors so you can find similar vacancies and resumes. A human makes the decision about a candidate; automatic screening without review must not be used.
- Matching job titles coming from different sources
- Finding similar vacancies and resumes by meaning
- Cleaning up the company job title reference list
- Sizes
- 109M – 278M
- Hardware
- from: Laptop
Image + textGGUF2025
Moonshot AI · China
An efficient MoE vision model (16B, 3B active) with a long context and a reasoning version. Handles long documents and video well.
- Analysing long PDFs and presentations
- Answering questions about video
- Operating interfaces from screenshots
- Sizes
- 16B-A3B
- Hardware
- from: 1 GPU
Satellite and geo2025
MBZUAI · UAE
A compact research model for satellite imagery, trained on both optical (Sentinel-2) and radar (Sentinel-1) data. Narrower in scope and community than Prithvi and TerraMind.
- Classification and segmentation of satellite imagery after fine-tuning
- A base for a land monitoring prototype
- Sizes
- TerraFM-B (ViT-Base)
- Hardware
- from: Laptop
Cybersecurity2022–2025
NVIDIA · USA
An open NVIDIA bundle: a card-transaction graph plus a classifier, a profile of normal user behaviour, log parsing and root-cause search. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
- Highlighting suspicious card operations taking participant links into account
- Tracking deviations of an account from its usual behaviour
- Parsing logs and finding the root cause of an incident
- Sizes
- from a few megabytes (tree-based models) up to BERT-based classifiers
- Hardware
- from: 1 GPU
Image generationGGUF2024–2025
BAAI (Beijing Academy of Artificial Intelligence) · China
An all-in-one model: generates, edits and moves an object or person from a photo into a new scene without separate plugins.
- Placing a product or person into a new scene
- Instruction-based photo editing
- Generation from multiple references
- Sizes
- about 4B
- Hardware
- from: 1 GPU
CybersecurityGGUF2023–2025
Clouditera · China
A Chinese open family for cybersecurity: reviewing vulnerabilities, analysing logs and traffic, explaining commands and scripts.
- Reviewing vulnerabilities and drafting fix recommendations
- Analysing logs and reconstructing an attack chain
- Explaining suspicious commands and scripts
- Sizes
- 1.5B – 14B
- Hardware
- from: Laptop
Photo editing2025
ByteDance Seed · China
ByteDance's video and photo restoration and upscaling. SeedVR2 does it in a single step, so it is noticeably faster than similar models. Commercial-friendly license.
- Upscaling photos and video to 2K–4K
- Restoring old videos and photos
- Enhancing user photos before publishing
- Sizes
- 3B – 7B
- Hardware
- from: 1 GPU
Robotics2025
Hugging Face · USA
A small robot control model that runs on a regular laptop. Trained on open data from the LeRobot community, suited to low-cost robot arms.
- Controlling a low-cost robot arm
- Quick robotization pilots and demos
- Training staff and students
- Sizes
- 450M
- Hardware
- from: Laptop
Text to SQLGGUF2025
IDEA Research · China
A text-to-SQL model trained with reinforcement learning: it works through the schema and the conditions step by step before producing a query.
- Database queries for questions with several conditions
- Reviewing and fixing other people SQL queries
- An analyst helper inside a BI system
- Sizes
- 3B – 14B
- Hardware
- from: Laptop
CybersecurityGGUF2025
Trendyol · Turkey
Security models from a large Turkish marketplace, published in GGUF format: reviewing alerts and incidents, English and Turkish.
- Reviewing alerts and first-pass incident assessment
- Explaining suspicious activity in reports
- Helping the on-duty shift of a monitoring centre
- Sizes
- 32B и 70B
- Hardware
- from: 1 GPU
Text to SQL2025
Snowflake · USA
A Snowflake model for turning questions into SQL, trained with reinforcement learning by checking query results. The open 7B version is based on Qwen2.5-Coder.
- Plain-language questions to a data warehouse
- Generating SQL for reports and dashboards
- Checking and fixing analysts' queries
- Sizes
- 7B
- Hardware
- from: Laptop
Image generationGGUF2025
ByteDance Seed · China
A unified model that understands images, generates them and edits them in a conversation. Similar to how images work in ChatGPT.
- Photo editing in a conversation
- Answering questions about an image
- Image generation with explanations
- Sizes
- 14B-A7B
- Hardware
- from: 1 GPU
TextOllama2025
DeepSeek · China
A reasoning model that thinks step by step before answering. Strong at calculations, logic and code; compact distilled versions are available.
- Complex calculations and logic checks
- Analysis of contracts and internal policies
- Help for developers
- Sizes
- 1,5B – 671B
- Hardware
- from: Laptop
Acoustic monitoring2024–2025
Shanghai Jiao Tong University and Peng Cheng Laboratory · China
A self-supervised sound understanding model that is markedly cheaper to train on your own data than its predecessors. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- Training your own audio model on modest hardware
- Audio features for spotting abnormal operating modes
- Labelling sound events on a site
- Sizes
- 90M (base) and 309M (large)
- Hardware
- from: Laptop
CodeRU2025
MTS AI (MWS AI) · Russia
A small coding assistant from MTS AI that understands requests in Russian. Runs locally, with plugins for VS Code and JetBrains.
- Code suggestions and completion in the editor
- Code explanations in Russian
- Drafts of tests and documentation
- Sizes
- 1.5B
- Hardware
- from: Laptop
Text analysisRU2023–2025
deepvk (VK) · Russia
Russian encoders from the VK team: RuModernBERT reads long texts, USER produces vectors for search, GeRaCl classifies texts by topic without training.
- Classifying requests without labeled data
- Knowledge base search in Russian
- Analyzing long contracts
- Sizes
- 35M – 360M
- Hardware
- from: Laptop
CodeGGUF2025
ByteDance Seed · China
A compact 8B coding model from ByteDance in base, instruct and reasoning versions. Its training data was selected by the model itself, with almost no hand-written rules.
- Code autocompletion and generation
- Solving algorithmic problems
- A base for fine-tuning on your own stack
- Sizes
- 8B
- Hardware
- from: Laptop
Forecasting2025
THUML, Tsinghua University · China
A forecasting model that returns a set of possible scenarios rather than a single line — useful when you need a range for demand or load, not one number.
- Forecasting demand with a range of values
- Planning stock while accounting for spread
- Forecasting load on services and staff
- Sizes
- 128M (sundial-base)
- Hardware
- from: Laptop
Acoustic monitoring2024–2025
MIT CSAIL and MIT-IBM Watson AI Lab · USA
A sound understanding model built on state spaces instead of a transformer: it handles recordings hours long, which suits continuous listening to a production line. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- Processing long continuous recordings
- Finding a rare event across a multi-hour shift
- Labelling sound events on a site
- Sizes
- 30M (small) and 49M (medium)
- Hardware
- from: Laptop
Voice assistants2025
Moonshot AI · China
A general-purpose audio model: speech recognition, answering questions about sounds, detecting emotions and voice dialogue. Trained on 13 million hours of audio; languages are English and Chinese.
- Speech recognition
- Detecting emotions and sound events
- Speech-to-speech voice dialogue
- Sizes
- 7B
- Hardware
- from: 1 GPU
Moderation and safety2023–2025
Falconsai and Freepik · USA and Spain
Small models that tell explicit images from regular ones. The Freepik model distinguishes four levels of explicitness. They run on a CPU.
- Filtering user photos and avatars
- Checking generated images before publishing
- Labeling a media library
- Sizes
- 86M
- Hardware
- from: Laptop
Image + textGGUF2024–2025
Hugging Face · France / USA
The smallest vision models from Hugging Face, starting at 256M; they run in a browser and on a phone. SmolVLM2 also understands video.
- Describing photos and video on low-end hardware
- Reading simple documents
- Embedding in mobile and offline apps
- Sizes
- 256M – 2.2B
- Hardware
- from: Laptop
Computer-use agentsGGUF2025
ByteDance Seed · China
A model that looks at a screenshot and controls the mouse and keyboard itself: clicks, fills in fields, navigates menus. The first generation and 1.5-7B are open; UI-TARS-2 weights were not released.
- Working in legacy software without an API
- Filling in forms and moving data between systems
- UI autotests from plain-language scenarios
- Sizes
- 2B – 72B
- Hardware
- from: Laptop
Text to SQL2025
Alibaba · China
Alibaba models for turning questions into SQL, based on Qwen2.5-Coder. They work with different SQL dialects; a small 3B version suits modest hardware.
- Plain-language database questions
- Queries for different databases (PostgreSQL, MySQL, SQLite)
- Automating routine reports
- Sizes
- 3B – 32B
- Hardware
- from: Laptop
Deepfake detection2025
Desklib · India
A recent open AI-text detector on DeBERTa-v3-large, trained on the RAID dataset, with a separate version for academic work. It errs in both directions - a human always reviews the result.
- Checking submitted articles and reports
- Filtering templated reviews and applications
- First-pass check of student work
- Sizes
- 0.4B (DeBERTa-v3-large)
- Hardware
- from: Laptop
Finance2025
Shanghai University of Finance and Economics (SUFE) · China
A reasoning model for financial tasks based on Qwen2.5-7B: calculations, report analysis, regulatory questions. Trained on Chinese and English data.
- Financial calculations with step-by-step explanations
- Answering questions about financial statements
- Analyzing tables of financial data
- Sizes
- 7B
- Hardware
- from: Laptop
Math and reasoningGGUF2025
Qihoo 360 · China
Reasoning models from Qihoo 360: a standard Qwen2.5 was fine-tuned for long reasoning using an open recipe; data and code are published.
- Calculations and formula checks
- Working through problems step by step
- A base for your own reasoning fine-tuning
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
Avatars2024–2025
Tencent Music (Lyra Lab) · China
Real-time lip sync: matches the mouth in a video to new audio. Suits video translation and live avatars.
- Dubbing video into another language
- Live avatar in a video chat
- Editing speech in a finished video
- Sizes
- under 1B
- Hardware
- from: Laptop
Search and RAGRUOllama2024–2025
Nomic AI · USA
Fully open embeddings, with weights, data and training code. v2 is multilingual on MoE; there are versions for code and for searching PDF pages.
- Search across documents and a knowledge base
- Code search
- Search across scans and PDFs without text recognition
- Sizes
- 137M – 7B
- Hardware
- from: Laptop
Text to SQL2025
Renmin University of China (RUC) · China
Models for turning questions into SQL, trained on millions of synthetic query examples across different databases. Three sizes for different hardware.
- Database questions without knowing SQL
- Generating queries for reports
- A base for fine-tuning on your own database schema
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
Video2024–2025
HPC-AI Tech · Singapore
A fully open video generation project: weights, code and training recipe. Version 2.0 at 11B makes video from text and from an image.
- Video from a text description
- Animating images
- Training your own video model
- Sizes
- up to 11B
- Hardware
- from: 1 GPU
Text to speechGGUF2025
Canopy Labs · USA
Language-model-based speech synthesis with lively intonation and emotional cues. Responds quickly, suitable for voice assistants. Mainly English.
- Real-time voice for an assistant
- Emotional voiceover
- Voice cloning
- Sizes
- 3B
- Hardware
- from: Laptop
Math and reasoningOllama2024–2025
Qwen (Alibaba) · China
Qwen's first open reasoning model: it thinks step by step before answering and comes close to DeepSeek-R1 on maths tasks with only 32B parameters.
- Calculations and formula checks
- Complex analytics with step-by-step breakdowns
- Checking the logic of contracts and internal policies
- Sizes
- 32B
- Hardware
- from: 1 GPU
Math and reasoningGGUF2025
Stanford University · USA
A reasoning model trained on just a thousand problems. It can be told to think longer to answer a hard question more accurately.
- Calculations and formula checks
- Working through complex problems step by step
- Training
- Sizes
- 1.5B – 32B
- Hardware
- from: Laptop
Image generationGGUF2024–2025
NVIDIA · USA
NVIDIA's fast image model: 4K images in seconds, runs even on a laptop GPU. The Sprint version generates in 1–2 steps.
- Bulk image generation
- High-resolution visuals
- Real-time generation inside apps
- Sizes
- 0.6B – 4.8B
- Hardware
- from: Laptop
Text to speechGGUF2025
Sesame · USA
A conversational speech model that takes the context of the conversation into account and sounds like a real person. English only.
- Voice for a conversational assistant
- Voicing dialogues
- Voice product prototypes
- Sizes
- 1B
- Hardware
- from: Laptop
Drawings and CADGGUF2025
ServiceNow Research, Mila and ETS Montreal · Canada
It turns a raster image into SVG code: instead of tracing pixels the model writes vector commands, so lines and symbols stay editable. It simplifies complex drawings, so the result needs a visual check.
- Vectorising diagrams, symbols and logos from raster images
- Turning scans of simple drawings into editable vectors
- Recovering icons and pictograms from images
- Sizes
- 1B and 8B
- Hardware
- from: Laptop
Video2025
StepFun · China
A large 30B video model producing clips of up to 204 frames. Needs server hardware, but is open under MIT.
- Video from a description
- Animating images
- Sizes
- 30B
- Hardware
- from: Cluster
Speech to textRUGGUF2022–2025
OpenAI · USA
Speech recognition in 99 languages, including Russian. The de facto standard for transcribing calls and meetings. Hugging Face's faster Distil-Whisper is English only.
- Transcription of calls and video meetings
- Video subtitles
- Voice messages to text
- Sizes
- 39M – 1,5B
- Hardware
- from: Laptop
TextGGUF2025
HUMAIN (formerly SDAIA) · Saudi Arabia
A Saudi model for Arabic and English, trained from scratch. One 7B version is openly available.
- An Arabic-language assistant
- Answering questions about documents
- Writing and editing texts in Arabic
- Sizes
- 7B
- Hardware
- from: Laptop
Plates and vehicles2023–2025
szad670401 (open project) · China
A well-known open system for Chinese plates: single-row blue and yellow plates, electric vehicles, driving-school cars. It has to be fine-tuned for the Russian plate format. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Plate recognition at entry and exit
- Running on modest hardware without a GPU
- Embedding recognition into your own application
- Sizes
- compact detection and reading models designed to run without a GPU
- Hardware
- from: Laptop
Text to speechGGUF2024–2025
hexgrad (independent developer) · not disclosed
A tiny speech synthesis model (82M) that sounds on par with large ones. Runs on a regular CPU; English and a few other languages, no Russian.
- Voicing articles and notifications
- Voice for apps without a GPU
- Bulk text voiceover
- Sizes
- 82M
- Hardware
- from: Laptop
Computer-use agentsGGUF2025
Microsoft Research · USA
An agent model that plans actions both in an interface (buttons on screen) and for a robot (arm movements). For now more of a research base than a finished product.
- Pilots in interface control
- Research projects spanning screens and robotics
- Analyzing screenshots with an action plan
- Sizes
- 8B
- Hardware
- from: 1 GPU
Robotics2024–2025
Stanford, Berkeley and partners · USA
The first large open vision-language-action model: a robot arm carries out commands like "put the apple in the bowl". OFT makes it several times faster.
- Controlling a robot arm by text command
- Pilots for robotizing simple operations
- Base for fine-tuning to your own robot
- Sizes
- 7B
- Hardware
- from: 1 GPU
Computer vision2023–2025
Google · USA
Models that map images and text into a shared space: you can search photos by words and classify images without training. OpenAI's CLIP (2021) is the predecessor.
- Image search by text query
- Automatic catalog labeling and tagging
- Filtering prohibited content
- Sizes
- about 0.2B to 2B
- Hardware
- from: Laptop
Math and reasoningGGUF2025
NovaSky (Sky Computing Lab, Berkeley) · USA
A Berkeley reasoning model trained for under 450 dollars. It showed that o1-preview-level reasoning can be reproduced with modest resources.
- Calculations and formula checks
- Working through problems step by step
- A base for your own reasoning fine-tuning
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
Photo editing2024–2025
Prama LLC · USA
A background removal model focused on difficult edges: hair, fur, fine details. The open version is MIT-licensed and can process video.
- Cutting out products and people from photos
- Background removal in video
- Preparing photos for a catalog
- Sizes
- about 95M
- Hardware
- from: Laptop
Search and RAGRU2023–2025
Alibaba · China
Alibaba embeddings and rerankers for search: from tiny to 7B based on Qwen2. There is a multilingual mGTE version with long context.
- Semantic search across documents
- Reranking search results
- Clustering and classifying texts
- Sizes
- 33M – 7B
- Hardware
- from: Laptop
Visual document search2025
LlamaIndex · USA
A small model for searching document pages as images, from the team behind a popular RAG framework. The card lists English, Italian, French, German and Spanish.
- Search across scans and PDFs without OCR
- Search across invoices, acts and contracts
- Picking pages for an AI assistant answer
- Sizes
- 2B (based on Qwen2-VL)
- Hardware
- from: 1 GPU
Text analysisGGUF2024–2025
Answer.AI and LightOn · USA / France
A modern replacement for classic BERT: faster, reads up to 8 thousand tokens at once. A base for your own classifiers. Trained on English and code; for Russian there is RuModernBERT.
- Classifying requests and documents
- Finding relevant passages in long texts
- Base for your own classifier after fine-tuning
- Sizes
- 150M – 395M
- Hardware
- from: Laptop
Search and RAGRUOllama2019–2025
UKP Lab (TU Darmstadt), later Hugging Face · Germany
The classic for meaning-based search: small, fast models that run even on a modest server without a GPU. The multilingual versions understand Russian.
- Search across a knowledge base and FAQ
- Finding similar tickets and duplicates
- Grouping reviews and requests by topic
- Sizes
- about 20M – 470M
- Hardware
- from: Laptop
Image + text2023–2025
Alibaba DAMO Academy · China
Models that watch a video and answer questions about it: what happens, when, who does what. VideoLLaMA 3 at 2B and 7B is among the strongest in its size class.
- Video description and short summary
- Finding a moment in a recording by question
- Tagging a video archive
- Sizes
- 2B – 72B
- Hardware
- from: Laptop
Computer vision2022–2025
University of Sydney and JD Explore Academy · Australia / China
A simple, accurate model for human pose estimation via keypoints. ViTPose++ handles human, animal and whole-body poses; built into the Transformers library.
- Body keypoints in photos and video
- Motion analysis in sports and rehabilitation
- Monitoring work postures and safety practices
- Sizes
- 33M – about 1B
- Hardware
- from: Laptop
Deepfake detection2024
Meta · USA
An imperceptible mark in synthetic speech plus a fast detector that finds it even inside a fragment of a long recording. The detector errs in both directions: a hit is a reason for a human to check, not proof.
- Marking speech synthesized by your service
- Finding your own mark in third-party publications
- Checking whether synthesis was mixed into a call recording
- Sizes
- a watermark generator and detector, 16-bit message
- Hardware
- from: Laptop
Visual document search2024
Alibaba (Tongyi Lab) · China
One vector for text, for an image and for a text-image pair: a single model can find a product by photo, a document page by question and an image by description. The card lists English and Chinese.
- Finding a product by photo
- Search across a catalogue of images and cards
- Search across document pages as images
- Sizes
- 2B and 7B
- Hardware
- from: 1 GPU
Search and RAGRUOllama2024
Snowflake · USA
Snowflake embeddings built specifically for search. Version 2.0 is multilingual (Russian is on the language list), handles long texts up to 8K tokens and can compress vectors.
- Search across documents and knowledge bases
- Picking passages for RAG
- Search across reports and internal data
- Sizes
- 22M – 568M
- Hardware
- from: Laptop
Documents and OCR2024
StepFun · China
One of the first general-purpose new-generation OCR models: text, formulas, tables, sheet music and diagrams. Small and runs on low-end hardware, but already behind newer models.
- Recognising scanned invoices and contracts
- Converting tables into an editable format
- Recognising formulas and diagrams
- Sizes
- 580M
- Hardware
- from: Laptop
TranslationRU2024
deepvk (VK) · Russia
Compact Kazakh-Russian translators from VK. At 197M they translate as well as the 600M NLLB and run on a regular CPU.
- Translating requests from Kazakh to Russian
- Translating documents and instructions into Kazakh
- Bilingual customer support
- Sizes
- 197M
- Hardware
- from: Laptop
Recommenders2024
Marqo · Australia
Models that turn a product photo and its title into a single vector: suitable for a similar-items block, image search and matching by description. Built for retail product cards.
- Similar items by photo and title
- Catalogue search by image
- Product search from a shopper phrase
- Sizes
- 203M (B) и 652M (L)
- Hardware
- from: Laptop
Text to speechGGUF2024
Hugging Face · USA
Speech synthesis where the voice is set by a text description ("a calm female voice, clean recording"). English and 8 European languages, no Russian.
- Choosing a voice by description
- Voicing videos
- Voice service prototypes
- Sizes
- 880M – 2.2B
- Hardware
- from: Laptop
Forecasting2024
IBM Research · USA
Tiny forecasting models from IBM: they run on an ordinary CPU and sit next to the business system without a separate GPU server.
- Forecasting sales and warehouse stock
- Forecasting energy use and equipment load
- Fast forecasts right on the company server
- Sizes
- very small: TinyTimeMixers have about 1M parameters
- Hardware
- from: Laptop
VideoGGUF2024
Genmo · USA
An open 10B video model with realistic motion. At release it was among the strongest open models; no updates now.
- Video from a description
- Short ad scenes
- Sizes
- 10B
- Hardware
- from: 1 GPU
Forecasting2024
Auton Lab, Carnegie Mellon University · USA
A foundation model for numeric series: one engine is used for forecasting, anomaly detection, filling gaps and classification.
- Forecasting demand and load
- Detecting anomalies in sensor readings and metrics
- Filling gaps in historical data
- Sizes
- about 40M – 385M
- Hardware
- from: Laptop
Visual document search2024
LightOn · France
A reranker for document pages as images: after a visual search it reorders the found pages by how well they answer the question. The card does not state the languages.
- Refining search results over scans and PDFs
- Selecting pages before an AI assistant answers
- Sorting retrieved slides and reports
- Sizes
- 2B (based on Qwen2-VL)
- Hardware
- from: 1 GPU
Cybersecurity2024
cybersectony · not disclosed
A very light classifier for emails and links showing signs of phishing. It errs in both directions, so borderline emails are still reviewed by a person.
- Flagging suspicious incoming emails
- Checking links from correspondence before opening them
- A first-level filter in a mail gateway
- Sizes
- about 66M
- Hardware
- from: Laptop
Finance2024
MIT and MIT-IBM Watson AI Lab · USA
Models that label suspicious chains of transfers by looking at who sent the money at the start of the chain and who received it at the end. A human makes the decision on a disputed operation; automatic blocking without review is not acceptable.
- Classifying transfer chains as ordinary or needing review
- Finding new suspicious chains in a large flow of operations
- Preparing material for the compliance team
- Sizes
- checkpoints from 0.1 to 45 MB
- Hardware
- from: Laptop
Video2022–2024
hzwer (Zhewei Huang) and co-authors · China
Generates intermediate frames: turns 24–30 fps into 60 fps and more and makes smooth slow motion. Versions 4.24+ smooth out video from generative models well.
- Increasing video frame rate
- Smooth slow-motion video
- Smoothing clips from AI generators
- Sizes
- lightweight model (size not stated on the model card)
- Hardware
- from: Laptop
Plates and vehicles2023–2024
dima806 (open project) · not disclosed
Two simple photo classifiers: vehicle type and car brand. Trained on public datasets, so check them on your own footage before use. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Identifying the vehicle type from a photo
- Pre-labelling the car brand
- Going through photos in listings and applications
- Sizes
- based on ViT-base (google/vit-base-patch16-224-in21k)
- Hardware
- from: Laptop
Visual document search2024
TIGER-Lab · Canada
Turns an image-plus-text model into an embedding model: one vector for a page, a diagram or a captioned photo. The card states English.
- Search across a mixed archive of texts and images
- Search across document pages as images
- Finding similar cards and illustrations
- Sizes
- about 4B (based on Phi-3.5-V)
- Hardware
- from: 1 GPU
Visual document search2024
University of Waterloo, Tevatron project · Canada
Searches page screenshots: the page is not OCRed but turned into a single vector, so the index is more compact than with late-interaction models. The card lists English and French.
- Search across scans and PDFs without OCR
- Search across presentations and reports with complex layouts
- Picking pages for an AI assistant answer
- Sizes
- 2B (based on Qwen2-VL)
- Hardware
- from: 1 GPU
Fact-checking and judges2024
Flow AI · not disclosed
A small judge model: it checks an answer against your instruction and gives a score with an explanation. Fits on a modest server. The judge itself makes mistakes and does not replace manual review.
- Checking AI assistant answers against the instruction
- Bulk scoring of exported conversations
- Quality control before rolling out changes
- Sizes
- 3.8B (based on Phi-3.5-mini)
- Hardware
- from: Laptop
Forecasting2024
The Time-MoE team · not disclosed
A forecasting model with a sparse architecture: only part of the network runs at each step, so it stays fast at a small size.
- Forecasting sales and stock levels
- Forecasting load on services and staff
- Planning purchases from history
- Sizes
- 50M and 200M
- Hardware
- from: Laptop
CodeOllama2024
01.AI · China
Coding models from 01.AI at 1.5B and 9B with a 128K-token context and support for 52 programming languages. A separate line next to the text Yi models.
- Code autocompletion and generation
- Explaining and refactoring code
- A programming assistant without the cloud
- Sizes
- 1.5B – 9B
- Hardware
- from: Laptop
RecommendersNot maintained2024
HKUDS, University of Hong Kong · China
Encoders that put a text portrait of a shopper and a text description of an item into one vector space so they can be matched directly. They help where a new listing has no purchase statistics yet.
- Recommendations for new items with no statistics
- Matching by a text portrait of the shopper
- Reinforcing ordinary recommendations with descriptions
- Sizes
- three RoBERTa-based versions: small, base, large
- Hardware
- from: Laptop
Image + textNot maintained2023–2024
Hugging Face · France / USA
Open vision models from Hugging Face that reproduced the closed Flamingo. Idefics3 became the basis for the compact SmolVLM line.
- Answering questions about images
- Analysing documents and screenshots
- A base for fine-tuning
- Sizes
- 8B – 80B
- Hardware
- from: 1 GPU
Documents and OCRNot maintained2024
Microsoft · USA
Turns a scanned page into tagged text with block coordinates, or into markdown. Handy as the first step before parsing a resume. A human makes the decision about a candidate; automatic screening without review must not be used.
- Converting resume scans into text that keeps its structure
- Preparing documents for field extraction
- Digitising paper forms
- Sizes
- about 1.4B
- Hardware
- from: 1 GPU
VideoNot maintained2023–2024
Shanghai AI Lab and CUHK · China
A module that brings Stable Diffusion image models to life, turning them into short animations. One of the first open video technologies.
- Short animations in brand style
- Animated covers and banners
- Animated stickers
- Sizes
- motion module on top of SD 1.5 / SDXL
- Hardware
- from: Laptop
RerankersGGUFNot maintained2023–2024
BAAI (Beijing Academy of Artificial Intelligence) · China
Rerankers: they take passages found by search and reorder them by how well they actually match the question. v2-m3 is multilingual and lightweight, often paired with bge-m3.
- Refining search results before a chatbot answers
- Sorting knowledge base search results
- Selecting the most relevant clauses of contracts and policies
- Sizes
- 278M – 9B
- Hardware
- from: Laptop
Image generationNot maintained2023–2024
Lvmin Zhang (Stanford) and the community · USA
An add-on for image models: sets pose, outlines, depth or floor plan so the result follows the required composition exactly.
- Image from a sketch or outline
- Keeping pose and composition
- Interior visualization from a floor plan
- Sizes
- 0.4B – 1.3B
- Hardware
- from: Laptop
Fact-checking and judgesNot maintained2023–2024
Vectara · USA
A small model that checks whether an AI answer is grounded in the source text or made up. Runs on a CPU and works well as a filter in RAG systems.
- Checking knowledge base chatbot answers for fabrications
- Quality control of document summaries
- Comparing language models by their tendency to make errors
- Sizes
- 110M
- Hardware
- from: Laptop
AvatarsNot maintained2024
Kuaishou (Kling) · China
Animates a portrait from a reference video: an actor's facial expressions and head turns are transferred to the photo. Runs fast even on a weak GPU.
- Animating portraits
- Transferring an actor's expressions to a character
- Mascot animation
- Sizes
- under 1B
- Hardware
- from: Laptop
Text analysisRUNot maintained2020–2024
SberDevices (ai-forever) · Russia
Sber's Russian-language encoders trained on large Russian corpora. A base for classifiers, NER and semantic search in Russian.
- Classifying requests in Russian
- Extracting names, amounts and dates after fine-tuning
- Detecting review sentiment
- Sizes
- about 30M to 430M
- Hardware
- from: Laptop
Image + textNot maintained2024
Microsoft · USA
A very small vision model: captions, object detection, segmentation and text reading from a single prompt. Runs even on a CPU.
- Reading text in photos
- Finding and highlighting objects
- Automatic photo captions
- Sizes
- 0.23B – 0.77B
- Hardware
- from: Laptop
Moderation and safetyGGUFNot maintained2024
Ai2 (Allen Institute for AI) · USA
An open Ai2 filter: in a single pass it determines whether a request is harmful, whether a reply is harmful, and whether the bot refused needlessly. Works in English.
- Checking requests to the bot
- Checking bot replies
- Finding unnecessary bot refusals on harmless questions
- Sizes
- 7B
- Hardware
- from: 1 GPU
RecommendersNot maintained2024
UC San Diego (McAuley Lab) · USA
Light encoders trained on pairs of item card and real review: they produce item vectors for similar-item blocks and for search by a shopper description. The weights are small and run on an ordinary server.
- A similar-items block based on descriptions
- Product search from a shopper phrase
- Suggesting cards for new listings
- Sizes
- 125M и 355M
- Hardware
- from: Laptop
Photo editingNot maintained2024
Lvmin Zhang (author of ControlNet) · USA
Changes lighting in a photo: relights an object or person from a description or to match a given background, so a cut-out looks natural.
- Matching product lighting to a new background
- Studio lighting for portraits without a reshoot
- Consistent lighting style across a catalog
- Sizes
- based on SD 1.5
- Hardware
- from: Laptop
Deepfake detectionNot maintained2024
UC Santa Barbara and co-authors · USA
A Longformer-based AI-text detector: it holds a long document whole and was trained on texts from many different language models. It errs in both directions; its output is a reason for a human to check.
- Checking long articles and reports as a whole
- Filtering machine text in a publication flow
- Comparing detectors on your own data
- Sizes
- about 150M (Longformer-base)
- Hardware
- from: Laptop
Photo editingNot maintained2023–2024
Shanghai AI Laboratory (OpenMMLab) and Tsinghua University · China
All-round photo inpainting: remove an object, insert a new one from a description, change a shape or extend the frame beyond its edges.
- Removing and replacing objects in photos
- Extending the frame to a required format
- Inserting a product or detail from a text description
- Sizes
- based on SD 1.5
- Hardware
- from: Laptop
TextNot maintained2024
Equall · France
Language models for legal texts, fine-tuned on US and European legal corpora (based on Mistral and Mixtral). English only.
- Reviewing English-language contracts
- Spotting risks and non-standard terms
- Drafting legal memos
- Sizes
- 7B – 141B
- Hardware
- from: Laptop
TextOllamaNot maintained2023–2024
01.AI · China
Bilingual (English and Chinese) 01.AI models of 6–34B, with versions supporting up to 200K tokens of context. No new open releases since 2024.
- Chat assistant on a single GPU
- Analysis of long documents
- Classification and data extraction from text
- Sizes
- 6B – 34B
- Hardware
- from: Laptop
MedicineGGUFNot maintained2024
Avignon University and Nantes University · France
Mistral 7B fine-tuned on PubMed Central papers, plus several merges with the general model. Compact and easy to run. Does not replace a doctor; decisions are made by a specialist.
- Searching and summarising medical papers
- Draft reference materials for staff
- Explaining medical terminology
- Sizes
- 7B
- Hardware
- from: Laptop
Text to SQLGGUFNot maintained2024
Chat2DB · China
A text-to-SQL model from the open Chat2DB database client: it supports different SQL dialects, with an English and Chinese model card.
- Turning a question into SQL inside a database client
- Drafting queries for different database engines
- Hints for developers working with a schema
- Sizes
- 7B
- Hardware
- from: Laptop
Text analysisRUNot maintained2023–2024
CIS, LMU Munich · Germany
Detects which language a text is written in: the third version covers more than two thousand labels, including Tatar, Bashkir, Chuvash, Udmurt, Mari, Erzya, Komi and other languages of Russia.
- Sorting mixed text archives by language
- Filtering out noise and foreign languages before training
- Routing requests to the right operator or model
- Sizes
- a FastText model; parameter count is not stated on the model card
- Hardware
- from: Laptop
3DNot maintained2024
Tencent ARC · China
Builds a 3D mesh from a single image in about 10 seconds: first it draws the object from several angles, then assembles the model from them.
- 3D model of an object from a photo
- Assets for games and visualizations
- Prototypes for 3D printing
- Sizes
- size not stated on the model card
- Hardware
- from: 1 GPU
Text to speechNot maintained2024
MyShell and MIT · USA
Lightweight multilingual speech synthesis that keeps up in real time on an ordinary CPU. English with accents, Spanish, French, Chinese, Japanese and Korean; no Russian.
- Voicing bot replies in foreign languages
- Voicing training materials
- Reading texts aloud on a server without a GPU
- Sizes
- small, runs in real time on a CPU
- Hardware
- from: Laptop
Text analysisNot maintained2024
University of Southern Denmark · Denmark
Turns a free-form occupation description into a standard HISCO code in 13 languages. Built for historical archives, but also useful for cleaning up job title reference lists. A human makes the decision about a candidate; automatic screening without review must not be used.
- Mapping mixed occupation names onto a single code
- Processing archives of HR and statistical data
- Preparing data for reporting
- Sizes
- based on CANINE-s, size not stated on the model card
- Hardware
- from: Laptop
Voice: speakers and soundNot maintained2024
MyShell and MIT · USA
Instant voice cloning from a short sample with control over emotion and accent; V2 speaks several languages. Use only with the voice owner's consent.
- Voicing videos with the company narrator's voice
- Voice bot with a recognizable brand voice
- Transferring timbre onto existing speech synthesis
- Sizes
- under 1B
- Hardware
- from: Laptop
Image generationNot maintained2023–2024
Huawei Noah's Ark Lab and partners · China
A compact 0.6B image model with quality on par with much larger ones. The Sigma version does 4K; suits modest hardware.
- Illustrations for articles and social media
- Backgrounds for product cards
- Quick visual drafts
- Sizes
- 0.6B
- Hardware
- from: Laptop
Fact-checking and judgesNot maintained2023–2024
KAIST and LG AI Research (prometheus-eval) · South Korea
An open judge model: it scores other models' answers against your criteria and explains the score. A replacement for paid models in the reviewer role.
- Scoring chatbot answers on your own scale
- Comparing two answer options
- Quality checks before launching an AI service
- Sizes
- 7B – 8x7B
- Hardware
- from: Laptop
TextOllamaNot maintained2023–2024
Hugging Face (H4) · USA
Hugging Face educational chat models based on Mistral, Gemma and Mixtral with an open fine-tuning recipe. Zephyr 7B Beta showed a small model can be trained to large-model level without human labeling.
- Lightweight chat assistant
- Reference and starting point for your own fine-tuning
- Drafts of texts and replies
- Sizes
- 7B – 141B-A35B
- Hardware
- from: Laptop
TextRUNot maintained2023–2024
Sber (ai-forever) · Russia
Sber's Russian text-to-text model, successor to ruT5 (2021). Small and fast: fine-tuned for summarizing, paraphrasing and fixing errors in Russian text; ready-made SAGE spell-checking versions exist.
- Fixing spelling mistakes and typos in Russian text
- Short summaries and paraphrasing
- Normalizing requests and inquiries before processing
- Sizes
- 95M – 1.7B
- Hardware
- from: Laptop
Deepfake detectionNot maintained2023–2024
Sichuan University and co-authors · China
An open model for finding forgeries in images: it outputs a pixel-level mask of altered regions. It errs in both directions; its map is a hint for an expert, not proof of a forgery.
- Finding pasted and erased fragments in photos
- Checking document scans for edits
- A baseline when comparing manipulation-localization models
- Sizes
- a Vision Transformer based model
- Hardware
- from: 1 GPU
TextOllamaNot maintained2023–2024
TinyLlama (SUTD researchers) · Singapore
A 1.1B model with the Llama 2 architecture, trained on 3 trillion tokens. Now behind newer small models, but still a popular base for experiments and fine-tuning.
- Simple chatbots on low-end hardware
- Experiments and team training
- A base for fine-tuning on a narrow task
- Sizes
- 1.1B
- Hardware
- from: Laptop
CybersecurityGGUFNot maintained2023–2024
ZySec AI · India
A small open assistant for security professionals: questions about standards, reviewing threats and vulnerabilities, drafting internal documents.
- Answering questions about security policies and standards
- First-pass review of threat reports
- Drafting internal protection guidelines
- Sizes
- 2.8B и 7B
- Hardware
- from: Laptop
Search and RAGRUNot maintained2022–2024
Microsoft · USA
Proven models for semantic search. The multilingual versions work well with Russian and are still a reliable base for RAG.
- Search across a knowledge base and documents
- Finding answers for a chatbot (RAG)
- Finding similar requests and duplicates
- Sizes
- 33M – 7B
- Hardware
- from: Laptop
ForecastingNot maintained2024
ServiceNow, Mila and partners · Canada
One of the first open out-of-the-box forecasting models. Tiny, gives a probabilistic forecast, now behind Chronos and TimesFM.
- Probabilistic sales forecast
- Quick forecasting pilots
- Baseline model for comparison
- Sizes
- 2.4M
- Hardware
- from: Laptop
Documents and OCRNot maintained2024
Microsoft · USA
One model for every document task: reading, answering questions about a page, extracting fields, classification. In HR it is used to parse resumes and attached scans. A human makes the decision about a candidate; automatic screening without review must not be used.
- Extracting fields from a resume and its attachments
- Answering questions about document content
- Classifying incoming documents
- Sizes
- 742M
- Hardware
- from: Laptop
Satellite and geoNot maintained2023–2024
Allen Institute for AI (Ai2) · USA
Pretrained models from the Satlas project for Sentinel-2, Landsat and high-resolution aerial imagery. The predecessor of OlmoEarth, still used in TorchGeo.
- Detecting objects in imagery: solar farms, wind turbines, ships
- Mapping roads and buildings from aerial photos
- A starting point for fine-tuning your own geo model
- Sizes
- Swin-v2 and ResNet backbones (Base)
- Hardware
- from: Laptop
Search and RAGRUOllamaNot maintained2024
BAAI · China
A model for meaning-based search in about a hundred languages. The core of RAG: the bot finds the right part of a document before answering.
- Search across a document base
- RAG for a chatbot
- Finding similar requests and duplicates
- Sizes
- 568M
- Hardware
- from: Laptop
RerankersNot maintained2023
NetEase Youdao · China
An embedding-plus-reranker pair for knowledge bases. The card lists English, Chinese, Japanese and Korean — Russian is not among the stated languages.
- Search across a knowledge base and reference materials
- Reordering retrieved passages
- Picking answers for a support chatbot
- Sizes
- about 280M
- Hardware
- from: Laptop
Photo editingNot maintained2023
Alibaba DAMO Academy · China
Colorizes black-and-white photos in natural colors. A lightweight model with a commercial-friendly license; a compact tiny version is available.
- Colorizing archival photos
- Color versions of historical photos for publications
- Family photo restoration service
- Sizes
- DDColor-T (tiny) and DDColor-L
- Hardware
- from: Laptop
TextOllamaNot maintained2023
Intel · USA
A fine-tuned Mistral 7B from Intel that showcased training and running on Intel CPUs and accelerators. Outdated; of interest as an example of optimisation for Intel hardware.
- A simple chat assistant
- Experiments with running on Intel hardware
- A base for fine-tuning
- Sizes
- 7B
- Hardware
- from: Laptop
Voice: speakers and soundNot maintained2023
Resemble AI · USA
A speech enhancement model: removes noise and restores lost frequencies so a muffled recording sounds studio-quality. Good for preparing a voice for voiceover.
- Restoring old and phone recordings
- Cleaning a voice before voiceover and cloning
- Improving audio in videos and podcasts
- Sizes
- under 1B
- Hardware
- from: Laptop
TranslationRUGGUFNot maintained2023
Google · USA
Google's translator for more than 400 languages under a permissive license. Russian is supported. A good substitute for NLLB when commercial use is needed.
- Translating documents and emails
- Translating catalogs and product descriptions
- Translating into CIS and Asian languages
- Sizes
- 3B – 10B
- Hardware
- from: Laptop
Documents and OCRNot maintained2022–2023
Microsoft · USA
Small models that find tables on PDF and scanned pages and restore their structure: rows, columns, headers. The text inside is read by a separate OCR.
- Finding tables in reports, statements and invoices
- Restoring rows and columns for export to Excel
- Preparing tabular data for analysis and RAG
- Sizes
- 29M
- Hardware
- from: Laptop
Music and soundNot maintained2023
LAION · Germany
CLIP for audio: maps audio and text into a shared space. Lets you search sounds and music by description and classify them without training. Text must be in English.
- Search sounds and music by description
- Automatic tags for an audio library
- Recognizing sound types (siren, breaking glass, voice)
- Sizes
- size not stated on the model card
- Hardware
- from: Laptop
Text to SQLNot maintained2023
RUCKBReasoning, Renmin University of China · China
An early line of open text-to-SQL models starting at 1B, including variants fine-tuned for specific database schemas.
- Turning an employee question into an SQL query
- Drafting warehouse queries for a report
- Embedding into a BI dashboard as a helper
- Sizes
- 1B – 15B
- Hardware
- from: Laptop
Photo editingNot maintained2022–2023
Taehoon Kim (POSTECH) · South Korea
A salient object detection model and the ready-made transparent-background tool built on it: removes backgrounds from photos, video and webcam with one command.
- Batch background removal from photos
- Replacing the background with a color or blur
- Background removal in video
- Sizes
- small (based on Swin-B)
- Hardware
- from: Laptop
Deepfake detectionNot maintained2022–2023
EURECOM · France
A step beyond AASIST: instead of raw audio it uses the wav2vec 2.0 speech encoder, which helps it hold up on unfamiliar synthesis methods. It errs in both directions - a human reviews the result.
- Spotting synthetic speech in calls
- Checking voice messages and recordings
- Fine-tuning for your own data and codecs
- Sizes
- about 0.3B (wav2vec 2.0 XLS-R encoder)
- Hardware
- from: Laptop
Voice: speakers and soundNot maintained2022–2023
Hendrik Schröter (University of Erlangen) · Germany
Lightweight real-time speech noise suppression that works even on a regular CPU and low-power devices. Removes hum, street and office noise while keeping the voice.
- Cleaning calls and voice messages of noise
- Preparing recordings before speech recognition
- Noise suppression for video calls
- Sizes
- about 2M
- Hardware
- from: Laptop
Photo editingNot maintained2022–2023
XPixel Group (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, and others) · China
Transformer-based photo upscaling, more accurate than SwinIR on fine details. Versions for real noisy photos and a lightweight HAT-S.
- Upscaling product and interior photos
- Preparing images for print
- Sharpening archival photos
- Sizes
- 9M – 40M
- Hardware
- from: Laptop
TextRUGGUFNot maintained2022–2023
Sber (ai-forever) · Russia
Sber's multilingual model covering 61 languages, including languages of the peoples of Russia and the CIS. Separate fine-tunes exist for Buryat, Yakut, Tatar, Bashkir, Kazakh and others, rare for open models.
- Texts in languages of the peoples of Russia and the CIS
- Base for fine-tuning on a less common language
- Drafts and templates in several languages
- Sizes
- 1.3B – 13B
- Hardware
- from: Laptop
TextRUGGUFNot maintained2023
SberDevices (ai-forever) · Russia
Separate mGPT versions, one per language: Bashkir, Buryat, Kalmyk, Mari, Ossetian, Tatar, Tuvan, Chuvash and Sakha. Each card also lists Russian and English.
- Generating and continuing text in a national language
- A base for fine-tuning to your own task
- Experiments with rare languages without training from scratch
- Sizes
- 1.3B
- Hardware
- from: Laptop
Text to speechRUGGUFNot maintained2023
Suno · USA
One of the first open models to voice text with intonation, laughter and pauses. Supports about ten languages, including Russian. Now outdated.
- Draft voiceovers for videos
- Voice service prototypes
- Sound effects in speech
- Sizes
- about 300M – 1B
- Hardware
- from: Laptop
Drawings and CADNot maintained2023
Google Research · USA
Small models that turn an image of a chart or diagram into a table of numbers and answer questions about it. Values read off an image are approximate, so the result has to be checked.
- Turning a chart from a report or PDF into a table
- Natural-language questions about a diagram
- A short text description of a chart
- Sizes
- 282M
- Hardware
- from: Laptop
TextRUGGUFNot maintained2023
Sber (ai-forever) · Russia
Sber's 13-billion-parameter base Russian model; GigaChat grew out of its fine-tuned version. Continues texts in Russian and English, context only 2048 tokens; today useful as a base for narrow fine-tuning.
- Base for fine-tuning on a narrow Russian-language task
- Generating template Russian texts
- Experiments with Russian-language models without license restrictions
- Sizes
- 13B
- Hardware
- from: 1 GPU
AvatarsNot maintained2023
Xi'an Jiaotong University and Tencent AI Lab · China
An older lightweight talking-head model: one photo plus audio becomes a video. Runs on weak hardware, but quality is noticeably below newer models.
- Talking photo for greetings
- Simple voiced avatars
- Sizes
- under 1B
- Hardware
- from: Laptop
3DNot maintained2022–2023
OpenAI · USA
Early open OpenAI models that create a 3D object from text or an image in seconds. Quality is basic, but they are fast and easy to run.
- Rough 3D mock-ups from a description
- Quick object prototypes for games and AR
- Training and research pilots in 3D
- Sizes
- 40M – 1B
- Hardware
- from: Laptop
RecommendersNot maintained2023
FashionCLIP research project (Farfetch data) · not disclosed
A time-tested model for clothing and footwear: it places an item photo and its description in one space, so it fits similar-item blocks and outfit matching. Fine-tuning for your own assortment is advisable.
- Similar items by photograph
- Building an outfit and matching add-ons
- Automatic tagging of clothing cards
- Sizes
- built on CLIP ViT-B/32
- Hardware
- from: Laptop
TextNot maintained2022–2023
Google · USA
Compact input-output models trained to follow instructions. Still used as a cheap base for classification, extraction and short answers.
- Classification of requests and documents
- Extracting fields from text
- Short answers and summaries
- Sizes
- 80M – 20B
- Hardware
- from: Laptop
Image + textNot maintained2023
Google · USA
Reads a document or a screenshot as an image and answers with structure: text, fields, answers to questions. In HR it is fine-tuned for resumes and forms. A human makes the decision about a candidate; automatic screening without review must not be used.
- Extracting data from resumes and forms supplied as images
- Questions about the content of a scan
- Parsing tables and diagrams in documents
- Sizes
- 282M – 1.3B
- Hardware
- from: Laptop
TextNot maintained2022–2023
EleutherAI · USA
Fully open models from the non-profit lab EleutherAI: GPT-NeoX-20B and the Pythia series with published intermediate training checkpoints.
- Base model for fine-tuning
- Research into model behavior
- Simple text generation and completion
- Sizes
- 70M – 20B
- Hardware
- from: Laptop
Acoustic monitoringNot maintained2022
Microsoft · USA
A self-supervised sound understanding model that became the base for many current systems: teams take it as a starting point and fine-tune it on their own equipment sounds. The system does not make a diagnosis, it gives you a reason to check the unit before it fails.
- A base for your own sound understanding model
- Audio features for spotting abnormal operating modes
- Labelling sound events on a site
- Sizes
- a ViT-base class model, around 90M parameters
- Hardware
- from: Laptop
RecommendersNot maintained2022
Rutgers University · USA
An early and still popular approach where recommendations are expressed as plain text: one small engine handles selection, rating and explanation. Checkpoints are trained on public datasets; a store needs its own.
- Suggesting the next item from history
- Predicting an item rating
- A text explanation of a recommendation
- Sizes
- small and base versions built on T5
- Hardware
- from: Laptop
Music and soundNot maintained2022
MIT · USA
A classic 2021 sound recognition model: detects 527 AudioSet event classes (siren, barking, breaking glass, music). Lightweight, runs without a GPU, in Transformers since 2022.
- Sound event recognition
- Tagging an audio archive
- Detecting alarm sounds
- Sizes
- about 87M
- Hardware
- from: Laptop
Documents and OCRNot maintained2022
SCUT DLVC Lab, South China University of Technology · China
A light model that takes both the text and the position of blocks on the page into account: trained in one language and transferable to others. Good for tagging fields in resumes and forms. A human makes the decision about a candidate; automatic screening without review must not be used.
- Tagging fields in resumes and forms
- Extracting data from forms and templates
- Parsing documents in several languages
- Sizes
- about 130M for the English version and about 280M for the multilingual one
- Hardware
- from: Laptop
Documents and OCRNot maintained2021–2022
Microsoft · USA
Recognizes a single line of text, including handwriting. The official weights are English only, but the model is often fine-tuned for other languages; there are community Russian versions.
- Recognizing handwritten lines in questionnaires and forms
- Recognizing printed lines after text detection on the page
- A base for fine-tuning to your own handwriting or font
- Sizes
- 62M – 608M
- Hardware
- from: Laptop
Documents and OCRNot maintained2022
NAVER CLOVA · South Korea
Reads a scanned document and returns a filled-in field structure straight away, with no separate OCR step. In HR it is fine-tuned for parsing resumes and forms. A human makes the decision about a candidate; automatic screening without review must not be used.
- Extracting fields from forms and resumes
- Parsing scans of certificates and diplomas
- Detecting the type of an incoming document
- Sizes
- about 200M
- Hardware
- from: Laptop
RerankersRUNot maintained2022
UKP Lab and the Sentence Transformers community · Germany
The most downloaded open rerankers: a tiny model reads a question-passage pair and scores how well they match. The multilingual mMARCO version covers Russian.
- Reordering knowledge base search results
- Selecting passages before a chatbot answers
- Finding duplicates among tickets and product cards
- Sizes
- about 4M – 120M
- Hardware
- from: Laptop
Computer visionNot maintained2021–2022
OpenAI · USA
The 2021 model that first linked images and text: search photos by words and classify them without training. English only; SigLIP 2 or PE are usually chosen today.
- Image search by text query
- Automatic tags for a catalog
- Finding similar images
- Sizes
- about 0.15B – 0.6B
- Hardware
- from: Laptop
Photo editingGGUFNot maintained2021–2022
Tencent ARC Lab · China
The classic for upscaling photos 2–4x while cleaning noise and compression artifacts. Lightweight, runs even on a CPU. Versions for drawings and anime.
- Upscaling old and small product photos
- Cleaning images of compression artifacts
- Preparing images for print
- Sizes
- about 17M
- Hardware
- from: Laptop
Photo editingNot maintained2021–2022
Tencent ARC Lab · China
Proven face restoration for old and compressed photos, with a commercial-friendly license. Often paired with Real-ESRGAN; the most used versions are 1.3 and 1.4.
- Restoring faces in old photos
- Enhancing avatars and profile photos
- Restoration in a photo shop or online service
- Sizes
- small, up to 0.1B
- Hardware
- from: Laptop
Computer visionRUNot maintained2022
Sber AI and SberDevices (ai-forever) · Russia
A Russian version of CLIP: matches images with Russian captions. Lets you search photos by description and sort images into categories without training.
- Product search by photo and by Russian description
- Sorting images into categories without labeling
- Checking that a photo matches its caption
- Sizes
- 150M – 430M
- Hardware
- from: Laptop
Text analysisRUNot maintained2019–2022
Meta · USA
A classic multilingual encoder for 100 languages, including Russian. The base of many sentiment, NER and embedding models, including BGE-M3.
- Detecting review sentiment in different languages
- Extracting names and organizations after fine-tuning
- Classifying requests
- Sizes
- 270M – 10.7B
- Hardware
- from: Laptop
Deepfake detectionNot maintained2021
NAVER Clova AI Research and EURECOM · South Korea
The baseline open model against voice spoofing: it listens to the raw recording and tells a live person from synthesis or a replay. It errs in both directions - its output is a reason for a human to check, not proof.
- Voice check during phone authentication
- Filtering replays and synthesis in a voice menu
- A baseline when comparing voice detectors
- Sizes
- weight files of 0.4 and 1.3 MB
- Hardware
- from: Laptop
Text analysisRUNot maintained2021
Microsoft · USA
A time-tested encoder behind many classifiers and NER models (including GLiNER). The multilingual mDeBERTa-v3 understands Russian.
- Classifying review sentiment
- Entity extraction after fine-tuning
- Checking whether a conclusion follows from a text
- Sizes
- 70M – 435M
- Hardware
- from: Laptop
Text analysisRUNot maintained2021
David Dale (cointegrated) · Russia
A very small Russian-English BERT that runs fast on a regular CPU. Ready-made fine-tuned versions exist for sentiment, toxicity and emotions.
- Detecting review sentiment
- Filtering rude chat messages
- Fast classification of requests
- Sizes
- 12M – 29M
- Hardware
- from: Laptop
Photo editingGGUFNot maintained2021
Samsung AI Center Moscow (with Skoltech) · Russia
Removes unwanted objects, text and watermarks from photos with clean background fill. Lightweight and fast; still the standard for this task.
- Removing price tags, people and clutter from photos
- Cleaning interior and real estate photos
- Removing text and dates from archival photos
- Sizes
- about 51M
- Hardware
- from: Laptop
Photo editingNot maintained2021
ETH Zurich · Switzerland
A transformer model for upscaling, denoising and removing JPEG artifacts from photos. Lightweight and proven; often embedded in other systems.
- Photo upscaling
- Image denoising
- Removing compression artifacts
- Sizes
- about 12M
- Hardware
- from: Laptop
TranslationRUGGUFNot maintained2020–2021
Meta · USA
An early Meta translator that translates directly between 100 languages, without English in the middle. Russian is supported. Old, but light and permissively licensed.
- Translation between any pair of 100 languages
- Quick draft translation on modest hardware
- Base for fine-tuning to your subject area
- Sizes
- 418M – 12B
- Hardware
- from: Laptop
FinanceNot maintained2020
Prosus · Netherlands
A classic model that determines the tone of financial news: positive, negative or neutral. English only, runs fast on a CPU.
- Scoring the tone of company news
- Labeling reports and press releases
- Signals for analytics dashboards
- Sizes
- 110M
- Hardware
- from: Laptop
Deepfake detectionNot maintained2020
MiniVision Technology · China
Practically the only fully open weight set for single-frame face liveness: it tells a live person from a photo, a screen or a mask. It errs in both directions - a person must be able to appeal a rejection.
- Liveness check when signing in by selfie
- Protecting an access system from a photo on a phone
- A check during remote customer identification
- Sizes
- two models of about 1.8 MB each
- Hardware
- from: Laptop
