3D2026
Sperid Labs · not stated
From a single picture of an object it makes a three-dimensional model in the form of Gaussian splats (the 3DGS .ply format). It takes a render, a generated image or a photo, removes the background itself, frames the object and fills in sides that the shot does not show, up to a million Gaussians. It runs on an ordinary graphics card with 7.2 GB of memory, in two seconds according to the authors. There are modes for renders and for photographs. The result opens in any splat viewer. The weights are Apache 2.0, but running it needs two gated encoders (DINOv3 and the VAE from FLUX.2-dev) with their own terms, which affects commercial use.
- quick 3D previews of products from one photo for cards and catalogs
- three-dimensional drafts from generated images
- object prototypes for games and AR
- Sizes
- about 3 GB of weights
- Hardware
- from: 1 GPU
Video2026
Pika Labs · USA
A Pika video model built on the open MiniMax H3 weights: it makes video with stereo sound at once in six steps and takes up to 12 reference materials (images, video, audio) that set the shot direction. Two adapters: FL2VA for text and the first and last frames, Ref2VA for reference materials. Locally it runs at 480p and 768p, while 1080p, 2K and 4K, audio stems and prompt enhancement are available only through the paid Pika API. It suits multi-shot stories, motion graphics and product films. The license inherits the MiniMax H3 terms and does not apply in the EU, the UK, South Korea and the USA, which has to be checked before use. Running it needs server-grade graphics cards.
- ads and product films with ready sound
- animation from reference images and video, multi-shot stories
- motion graphics and title sequences
- Sizes
- 33B (a fine-tune of MiniMax H3, adapters)
- Hardware
- from: Cluster
Text analysisRU2026
Liquid AI · USA
Small decision models: from text, an image or a voice clip they answer yes or no, pick an option or give a rating in one pass, without writing text. d1-3B sees images, d1-omni-600M also hears speech up to 30 seconds. Russian is listed. The open d1-2B (text, pictures and video, based on LFM3-VL-2B) and d1-Omni-2B (sound as well) decide in milliseconds, 5.7 ms on an H100 by the authors measurements; besides choosing an answer they pull out text, numbers and dates with their positions and find objects in a picture. It is not a chat model.
- routing requests and tickets to teams
- checking a photo for defects or violations against a list of questions
- routing voice commands
- Sizes
- 600M, 2B and 3B
- Hardware
- from: Laptop
TextRUOllama2025–2026
Liquid AI · USA
Models with a new architecture for on-device use: fast on a regular CPU and on phones. Versions for data extraction, RAG and tools, plus LFM2.5-VL for images and voice LFM2.5-Audio. The largest, LFM2.5-24B-A2B (2.45B active, 131K-token context, Russian in the language list), always reasons before answering and targets fast on-device agents. In October the LFM3 generation came out on a new tri-hybrid architecture: LFM3-1.7B for local agents (256 thousand tokens of context, about 1 GB of memory at 4 bits, pre-trained on 22 trillion tokens), LFM3-VL-2B for images, LFM3-Audio-2B for speech and LFM3-Omni-2B, which understands text, images, video and sound and answers in text and speech. The authors do not recommend it for complex code and multi-step reasoning.
- Offline assistant on a laptop or phone
- Data extraction from documents
- Tool calling in apps
- Sizes
- 230M – 24B-A2B
- Hardware
- from: Laptop
Image generation2026
Bria AI · Israel
A family of Bria image models: Fibo 2.0 dev draws from text, Fibo 2.0 edit turbo edits finished images from a description. According to the authors' paper, the model was trained on very detailed structured descriptions so that it follows a long brief better. The weights are free only for non-commercial work: advertising and sales need a separate Bria license. There are ready files for ComfyUI, including ones compressed to int8. The languages of prompts are not stated on the card.
- creating pictures from a detailed description for tests and prototypes
- editing finished pictures with a text command
- research and personal projects without commerce
- Sizes
- not stated (the bundle includes a Qwen3-VL 4B text encoder)
- Hardware
- from: 1 GPU
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
Forecasting2026
Mistral AI · France
A family of models for forecasting time series with no task-specific training: from the history of sales, demand or load it gives a forecast with intervals (21 quantiles). It takes up to 32 thousand points of history and forecasts up to 1024 steps at a time. By Mistral's measurements, the best zero-shot model on GIFT-Eval, TIME and fev-bench. Runs on a CPU.
- forecasting sales and demand from history
- forecasting load on a warehouse, a till, a call center
- assessing the risk of stock shortage or surplus from forecast intervals
- Sizes
- 5M, 28M, 123M and 209M
- Hardware
- from: Laptop
Image generationGGUF2024–2026
Black Forest Labs · Germany
Image generation from the creators of Stable Diffusion. Renders text in images well and keeps the composition. The new FLUX.3 Image Klein (5.6B) targets ordinary graphics cards: up to 4K at once, regional editing, up to ten references; access to the weights is granted automatically after signing in on Hugging Face.
- Images for product cards
- Banners and covers
- Photo editing by description (Kontext)
- Sizes
- 4B – 32B
- Hardware
- from: 1 GPU
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
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
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
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
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
Image generationGGUF2025–2026
Alibaba · China
Image generation and editing, including text in images. Earlier versions allow commercial use; the latest 2.1 is non-commercial only.
- Infographics for product cards
- Photo editing by text command
- Ad creatives
- Sizes
- 7B – 20B
- 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
Tabular data2026
Xiaomi · China
A small tabular model: it takes labeled rows as context and predicts values for new rows in one pass, with no task-specific training. Two checkpoints: classification and regression.
- forecasts from a table of customers or orders
- estimating price or demand from sales rows
- scoring requests without training a separate model
- Sizes
- about 70M
- 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
Plates and vehicles2020–2026
Mikel Brostrom (open project) · not disclosed
A set of trackers: it links the same vehicle across frames and cameras, which is how flow and time on site are counted. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Counting vehicles crossing a line
- Following a vehicle across frames
- Finding the same vehicle on another camera
- Sizes
- trackers plus re-identification models from compact to large
- Hardware
- from: Laptop
Faces2021–2026
InsightFace (deepinsight) · China
The most widely used open toolkit for face detection and recognition. Many identity-preserving image generators are built on it. The pretrained weights are non-commercial.
- Detecting and comparing faces in photos
- Face-based access in prototypes
- Face processing as part of other AI systems
- Sizes
- packages from 16 MB to 407 MB
- 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
Tabular data2025–2026
Stable AI (Beijing, with Tsinghua University) · China
A table model that alone can classify, predict numbers and fill in missing data. The lightweight LimiX-2M runs on an ordinary computer.
- Filling gaps in 1C and CRM exports
- Churn prediction and scoring
- Classifying customers and products
- Sizes
- 2M – 16M and LimiX-2
- 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
Tabular data2022–2026
Prior Labs (University of Freiburg) · Germany
A ready-made model for tables: it takes example rows and immediately predicts for new ones, without lengthy training or tuning. Only v2 is free for business; newer versions are non-commercial.
- Predicting customer churn from a CRM export
- Scoring applications and leads
- Classifying customers from 1C data
- Sizes
- from a few to hundreds of millions of parameters
- Hardware
- from: Laptop
TextRU2022–2026
Yandex · Russia
Yandex models trained from scratch with a focus on the Russian language and Russian context. The new AliceAI-Foundation 80B-A3B (Apache 2.0) is a base model only, with no instruct version: you fine-tune it for your own tasks. The efficient AliceAI-T5 35B-A0.6B is also available.
- Russian-language assistant and chatbot
- Answers based on the company knowledge base
- Base for industry-specific fine-tuning
- Sizes
- 8B – 100B
- Hardware
- from: Laptop
TextRUOllama2023–2026
Alibaba · China
A family of language models with strong Russian language support, from small versions for a laptop to a flagship on par with commercial APIs.
- Chatbot and knowledge-base assistant
- Replies to emails and customer requests
- Document parsing and classification
- Sizes
- 0,6B – 2,4T-A95B
- Hardware
- from: Laptop
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
Forecasting2024–2026
Google · USA
A ready-made Google forecasting model: forecasts any time series without training on your data.
- Sales and demand forecasting
- Purchase and inventory planning
- Load and traffic forecasting
- Sizes
- 200M – 500M
- 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
RerankersGGUF2024–2026
Jina AI · Germany
Strong multilingual rerankers; m0 also ranks pages as images (scans, slides). The latest versions are open for non-commercial use only.
- Refining search results before a chatbot answers
- Sorting retrieved PDF pages and slides
- Catalog and knowledge base search
- Sizes
- 33M – 2.4B
- Hardware
- from: Laptop
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
Video2024–2026
Lightricks · Israel
A fast video model; with LTX-2 it generates video with sound and speech in one go. Camera and pose control, lightweight versions available.
- Ad videos with sound
- Video from a product photo
- Voiced scenes for social media
- Sizes
- 2B – 22B
- 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
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
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
Image generationGGUF2026
Krea · USA
A 12B image model focused on realism without the glossy "AI look". The Turbo version produces a 2K image in a couple of seconds.
- Realistic photos for advertising
- High-resolution images
- Style fine-tuning
- Sizes
- 12B
- Hardware
- from: 1 GPU
Image + textOllama2024–2026
Moondream (M87 Labs) · USA
A small, fast vision model for product use cases: answering questions, finding and pointing to objects, captions. Moondream 3.1 is a 9B MoE with 2B active.
- Finding and counting objects in photos
- Checking photos from field reports
- Captions and tags for a catalogue
- Sizes
- 2B – 9B-A2B
- 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
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
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
Photo editing2023–2026
BRIA AI · Israel
BRIA's background removal, trained on licensed photos. Soft edges, hair, transparency. Video versions available. Business use requires a paid agreement.
- Cutting products out onto a white background
- Staff and expert photos without background
- Background removal in video
- Sizes
- 44M – 220M
- 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
Computer-use agentsGGUF2025–2026
H Company · France
A French model family for controlling a browser and computer: precisely finds the right element on screen and handles multi-step tasks. The latest Holo3 and 3.1 are open under Apache 2.0.
- Working in web portals and legacy software without an API
- Filling in forms and applications
- Testing interfaces against scenarios
- Sizes
- 0.8B – 235B-A22B
- Hardware
- from: Laptop
TranslationRU2025–2026
Tencent · China
Tencent translators for 33 languages; the first version won the WMT25 competition. Russian is supported. The small 1.8B version runs on a laptop; the new Hy-MT2 is under Apache 2.0.
- Translating documents while keeping formatting
- Translation with a set glossary of terms
- Translating correspondence with Chinese partners
- Sizes
- 1.8B – 30B-A3B
- Hardware
- from: Laptop
Search and RAGRUGGUF2023–2026
Jina AI · Germany
Strong multilingual embeddings with long context; v5-omni understands text, images and audio. Recent versions are open for non-commercial use only.
- Search across documents in many languages
- Search across images and scans
- Classification and clustering
- Sizes
- 33M – 3.8B
- 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
Computer vision2024–2026
Meta · USA
Meta's models for analyzing people in photos: pose keypoints, body part segmentation, normals and depth. Sapiens2 was trained at high resolution and adds human matting.
- Pose and body keypoint detection
- Segmentation of body parts and clothing
- Separating a person from the background
- Sizes
- 0.1B – 5B
- 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
Plates and vehicles2025–2026
MorseTechLab · not disclosed
The most downloaded plate detector on Hugging Face: it finds the plate in a frame, and a separate model then reads it. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Finding the plate in camera video
- Preparing crops for plate reading
- Testing a plate recognition idea without training
- Sizes
- a fine-tuned YOLO11, with an ONNX build available
- 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
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
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
Computer-use agents2024–2026
Show Lab (National University of Singapore) · Singapore
A lightweight model for working with interfaces: finds buttons and fields by description and performs actions on the web and on a phone. ShowUI-π can drag with the mouse.
- Clicking and filling in forms from a task description
- Web UI autotests
- An assistant on a low-end computer without the cloud
- Sizes
- 2B (ShowUI), about 500M (ShowUI-π)
- 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
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
TextRU2025–2026
Reka AI · USA
Compact Reka models: Flash 3 (21B) for reasoning and Reka Edge (7B), which quickly analyzes images and video on-device.
- Photo and video analysis (Edge)
- Object detection in images
- Reasoning tasks (Flash)
- Sizes
- 7B – 21B
- Hardware
- from: Laptop
Computer vision2023–2026
Meta · USA
Selects any object in photos and videos with a click or a box. The basis for background removal and object counting.
- Background removal from product photos
- Counting objects in photos
- Data labeling for training
- Sizes
- 91M – ~0,85B
- Hardware
- from: Laptop
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
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
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
TranslationRUOllama2026
Google · USA
Translators based on Gemma 3 for 55 languages that can also translate text in images. Russian is supported. The 4B version fits on a laptop.
- Translating documents and correspondence
- Translating text from screenshots and photos
- Localizing websites and apps
- Sizes
- 4B – 27B
- Hardware
- from: Laptop
Computer vision2023–2026
Ultralytics · USA
The most widely used real-time object detector: finds and marks items in video even on modest hardware. YOLOv5 came out back in 2020; the catalog starts from YOLOv8.
- Counting people, cars and goods on video
- Checking hard hats and workwear
- Spotting defects on the production line
- Sizes
- 2.4M – 68M
- 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
Computer-use agents2023–2025
Zhipu AI (Z.ai) and Tsinghua University · China
One of the first open models for controlling an interface from a screenshot; its successor, AutoGLM-Phone, works in Android smartphone apps.
- Automating actions in mobile apps
- Working in web interfaces without an API
- Testing apps against scenarios
- Sizes
- 9B – 18B
- Hardware
- from: 1 GPU
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
Computer vision2023–2025
Meta · USA
Meta's open reproduction of CLIP with a transparent data collection recipe. MetaCLIP 2 is trained on multilingual data from around the world. Non-commercial license only.
- Image search by text
- Image classification without training
- Search research and prototypes
- Sizes
- 0.15B – 3.6B
- Hardware
- from: Laptop
3DGGUF2025
Meta · USA
Reconstructs the 3D shape of an object or a human body from one ordinary photo, even when the object is partly hidden. Two models: Objects and Body.
- 3D model of an item from a catalog photo
- Estimating body pose and shape from a photo
- Try-on and AR scenarios
- Sizes
- size not stated on the model card
- Hardware
- from: 1 GPU
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
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
Computer vision2023–2025
IDEA Research · China
Finds any objects in an image from a text description, without training on your data: "red box", "person without a hard hat". Rex-Omni is the new VLM-based generation.
- Finding objects by description without labeling
- Automatic data labeling for training
- Checking photos against requirements
- Sizes
- 172M – 3B
- Hardware
- from: Laptop
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
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
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
3D2024–2025
Tencent · China
Tencent's open 3D line: shape and texture from an image, at the level of paid services. Omni adds control of pose and shape, Part splits a model into parts.
- Textured 3D product models
- Characters and objects for games
- Splitting a model into parts for printing
- Sizes
- set of models: shape and textures
- Hardware
- from: 1 GPU
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 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
Recommenders2024–2025
ByteDance · China
A two-level design: one language model reads the item description, the second builds the shopper interest from history. Ready checkpoints at 1B and 7B are published, but they need fine-tuning for your own catalogue.
- Recommendations from browsing and purchase history
- Understanding an item from its title and description
- Suggesting cards for new items with no statistics
- Sizes
- 1B, 7B
- Hardware
- from: 1 GPU
ForecastingGGUF2024–2025
Salesforce · USA
Salesforce's universal forecasting model for series with different frequencies and many variables. Weights are open for research only.
- Research forecasting pilots
- Comparison with other forecasting models
- Forecasts across many related series
- Sizes
- 11M – 311M
- Hardware
- from: Laptop
Virtual try-on2025
Kunbyte AI · China
Try-on beyond clothing: glasses, earrings, bags, hats, watches and other accessories. Works without a mask. Needs a GPU with 28 GB or more.
- Trying accessories and jewelry on a photo
- Product cards with an accessory on a model
- Online fitting room for eyewear and jewelry
- Sizes
- add-on for FLUX.1 Fill dev 12B
- 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
Virtual try-on2025
LavieAI and Sun Yat-sen University · China
Tries on several items at once: top, bottom, shoes, bag. Faster than earlier models thanks to caching. Non-commercial license.
- Building an outfit from several products on one model
- "Build a look" pilot on a website
- Lookbook prototypes without a shoot
- Sizes
- based on SD 1.5 inpainting
- Hardware
- from: 1 GPU
Plates and vehicles2024–2025
NYU Abu Dhabi (ComNets) · UAE
A model that looks at a photo and answers in words what the plate says: fine-tuned on Malaysian plates, so the Russian format needs fine-tuning. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Reading plates in difficult frames
- Answering questions about a vehicle photo
- Going through an archive of camera photos
- Sizes
- 3B
- Hardware
- from: 1 GPU
Plates and vehicles2023–2025
Hezar AI · Iran
Character reading for Iranian license plates; the model is small and runs without a GPU. It was trained on another country plates, so the Russian format needs fine-tuning. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Reading a plate from a cropped image
- Using the architecture as an example for your own plate format
- Fine-tuning reading on your own footage
- Sizes
- a compact CRNN model
- Hardware
- from: Laptop
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
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
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
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
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
Virtual try-on2024–2025
Sun Yat-sen University and Pixocial · China
A lightweight try-on model that runs on a regular GPU. There is a mask-free version and CatV2TON, which also tries clothes on in video.
- Trying a garment on a customer's photo
- Draft product cards on a model
- Try-on in a short video
- Sizes
- 899M
- Hardware
- from: Laptop
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
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
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
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
Virtual try-on2025
Beijing University of Posts and Telecommunications and others · China
An all-round FLUX-based apparel toolkit: try-on, generating a model wearing a given item, and "taking off" an item from a person into a separate product photo.
- Try-on from a product photo
- Photo of a model wearing an item from a text description
- Clean product photo extracted from a shot of a person
- Sizes
- add-ons (LoRA) for FLUX.1 dev 12B
- Hardware
- from: 1 GPU
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
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
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 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
3D2024–2025
Stability AI · UK
Stability AI models that turn a single photo into a textured 3D model in about a second. SPAR3D lets you adjust the shape through a point cloud.
- 3D product cards from photos
- Assets for games and AR
- Quick mock-ups for design
- Sizes
- 1B – 2B
- Hardware
- from: 1 GPU
Virtual try-on2024
Tencent and Fudan University · China
Tencent's transformer-based try-on: more accurately reproduces fabric texture, fine prints and garment length. Non-commercial license.
- Try-on of items with complex prints and textures
- Test product cards on a model
- Checking length and fit on a photo
- Sizes
- based on SD3
- Hardware
- from: 1 GPU
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
Virtual try-on2024
Meta AI (with King's College London) · USA
Meta's model for virtual try-on and changing a person's pose in a photo. Carefully transfers fine fabric details and lettering. MIT license, but the training data is non-commercial.
- Trying clothes on a model photo
- Changing the model pose in an existing shot
- Adding extra angles for a product card
- Sizes
- based on Stable Diffusion
- Hardware
- from: 1 GPU
Plates and vehiclesRU2022–2024
RIA.com · Ukraine
A plate recognition system with separate reading modules for Russia, Kazakhstan, Belarus, Ukraine, Georgia, Armenia and Kyrgyzstan. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Reading a Russian plate from a camera
- Identifying the country and plate type
- Logging vehicles at entry and exit
- Sizes
- a YOLOv8 detector plus separate character-reading modules
- 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
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
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
Image generationGGUF2022–2024
Stability AI · UK
The model that started open image generation. A huge ecosystem of fine-tunes, styles and plugins; runs even on a home PC. The popular SDXL-Lightning and Hyper-SD accelerators were made by ByteDance.
- Illustrations and banners for advertising
- Backgrounds and scenes for product cards
- Fine-tuning to a brand style
- Sizes
- 0.9B – 8B
- 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
Recommenders2024
Recombee · Czechia
Description encoders trained so that items people actually buy together end up close to each other, not merely items that sound alike. Versions trained on public catalogues are published.
- A frequently-bought-together block
- Recommendations for listings with no sales history
- Moving the model to a new catalogue
- Sizes
- about 110M (built on all-mpnet-base-v2)
- 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
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
RecommendersGGUFNot maintained2024
Ohio State University (NingLab) · USA
Three language models tuned on a large set of commerce instructions: product selection, answers from the item card, matching listings, review analysis. Your own assortment still needs fine-tuning.
- Finding a product from a shopper request
- Answering questions about an item card
- Matching identical listings across catalogues
- Sizes
- 2.7B – 13B
- Hardware
- from: Laptop
Tabular dataNot maintained2024
ML Foundations · USA
A foundation model for predictions on tables: it classifies and forecasts from a handful of examples, with no separate task-specific training.
- Classifying table rows from a few examples
- Predicting a value from a data row
- Quickly testing hypotheses on new datasets
- Sizes
- 8B
- Hardware
- from: 1 GPU
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
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
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
Text to SQLOllamaNot maintained2023–2024
Defog · USA
One of the first open models that turn a plain-language question into an SQL query against a database. Available in Ollama, but newer competitors are already stronger.
- Answering managers' questions from the sales database without an analyst
- Drafting SQL queries for reports
- An assistant inside a BI system
- Sizes
- 7B – 70B
- 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
Virtual try-onNot maintained2024
KAIST and OMNIOUS.AI · South Korea
One of the best-known open virtual try-on models: moves a garment from a product photo onto a photo of a person, keeping prints and logos well. Non-commercial license.
- Pilot of a fitting room on a store website
- Prototype product cards on a model without a photo shoot
- Comparison with commercial try-on services
- Sizes
- based on SDXL
- Hardware
- from: 1 GPU
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
RecommendersNot maintained2024
VinAI Research · Vietnam
A 7B language model further trained on review and product-card text for recommendation and rating-prediction tasks. The licence forbids commercial use; a store still needs its own order history.
- Predicting the rating a user would give an item
- Suggesting the next purchase from history
- Researching text-based recommendations
- Sizes
- 7B
- Hardware
- from: 1 GPU
Virtual try-onNot maintained2024
Xiao-i Research · China
An early popular open try-on model: one version for upper-body garments, another for full-length outfits. Non-commercial license.
- Trying tops on a model photo
- Full-length try-on: tops, bottoms, dresses
- Fitting room prototype for testing
- Sizes
- based on Stable Diffusion
- Hardware
- from: 1 GPU
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
Text to SQLGGUFNot maintained2024
ChatDB · USA
A text-to-SQL model built on DeepSeek-Coder, aimed at complex questions spanning several tables and conditions.
- Complex queries joining several tables
- Answering database questions without an analyst
- Drafting SQL for reports and exports
- Sizes
- 7B
- Hardware
- from: Laptop
Image generationNot maintained2023–2024
Playground AI · USA
An SDXL-based model focused on aesthetics: vivid colors, contrast, portraits. Compatible with SDXL ecosystem tools.
- Aesthetic ad visuals
- Portraits and lifestyle images
- Post covers
- Sizes
- about 2.6B
- Hardware
- from: 1 GPU
Virtual try-onNot maintained2024
KAIST · South Korea
A research try-on model from CVPR 2024, one of the first built on Stable Diffusion. Now mostly used as a comparison baseline.
- Pilot of upper-body garment try-on
- Comparing quality of different try-on models
- Training your own try-on on the open code
- Sizes
- based on Stable Diffusion
- Hardware
- from: 1 GPU
RecommendersNot maintained2023
Renmin University of China · China
An approach where every item gets a short identifier code that a language model understands, and the model predicts that code. Delta weights for three categories are published; no licence is stated on the card.
- Suggesting the next item from history
- Turning a catalogue into short codes for the model
- Recommendations from a shopper text request
- Sizes
- about 7B (a delta to LLaMA weights)
- Hardware
- from: 1 GPU
VideoNot maintained2023
Stability AI · UK
Stability AI's first open video model: turns a photo into a 2–4 second clip. Now behind newer models in quality.
- Animating product photos
- Short video intros
- Animating illustrations
- Sizes
- about 1.5B
- Hardware
- from: 1 GPU
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
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
Text to SQLGGUFNot maintained2023
Numbers Station · USA
One of the first open text-to-SQL lines, including very small versions from 350M that run on an ordinary PC.
- Turning a question into SQL from a table description
- Hints while writing queries
- A local analyst helper with no data leaving the company
- Sizes
- 350M – 7B
- Hardware
- from: Laptop
Text analysisRUNot maintained2022–2023
David Dale (cointegrated) and the community · Russia
Ready-made tiny rubert-tiny models for Russian text: detect rudeness and insults, sentiment and emotions. They run on a CPU in milliseconds.
- Filtering insults in Russian chats and comments
- Labeling reviews as positive, neutral or negative
- Spotting irritated customers in requests
- Sizes
- 12M – 29M
- 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
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
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
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
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
