TextRUOllama2024–2026
Cohere · Canada
Business models: document search with source citations, tool calling, many languages. Command A+ (2026) was the first under Apache 2.0, followed by the North line: code, translation and compact vision.
- Knowledge-base answers with source citations
- Agents that work with internal systems
- Translation and correspondence in different languages
- Sizes
- 2.5B – 218B-A25B
- Hardware
- from: Laptop
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.
- 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
TextRUOllama2023–2026
Mistral AI · France
European models focused on speed. Mixtral was one of the first open mixture-of-experts models; there are versions for images (Pixtral, Medium 3.5), Lean proofs and moderation (Shieldstral).
- Fast chat responses
- Data extraction from text
- Translation and multilingual work
- Sizes
- 3B – 675B
- Hardware
- from: Laptop
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
TextGGUF2025–2026
Moonshot AI · China
Very large Moonshot MoE models for agentic work. K3 (2.8 trillion parameters) was the largest open model at release, with up to 1M tokens of context and image understanding; K2.7-Code is built for programming.
- Multi-step agents: search, data collection, reports
- In-depth document analysis
- Help for developers
- Sizes
- 16B-A3B – 2.8T-A104B
- 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
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
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.
- 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
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
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
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
CodeGGUF2026
IQuest Research · China
A family of coding models with standard and reasoning versions, including a Loop variant that runs through its layers a second time. Sizes from 7B to 40B.
- Writing and refining code
- Solving tasks with step-by-step reasoning
- Agentic work with a repository
- Sizes
- 7B – 40B
- Hardware
- from: Laptop
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
CodeRUOllama2025
Mistral AI (with All Hands AI) · France
Mistral models for agentic development: they read the repository, edit files and run commands on their own. The 24B version fits on a single GPU.
- A developer agent that fixes tickets from the tracker
- Extending internal systems from a description
- Automating routine code edits
- Sizes
- 24B – 123B
- 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
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
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
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
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
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
Math and reasoningGGUF2024–2025
DeepSeek · China
DeepSeek models for formal proofs in Lean 4: the proof is checked by a program, not a person. A narrow tool for mathematicians and engineers.
- Formal verification of mathematical workings
- Verifying algorithm correctness
- Training and olympiad preparation
- Sizes
- 7B – 671B
- 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
CybersecurityGGUF2023–2025
Kindo · USA
One of the best-known open families for security and DevSecOps work: reviewing code for weaknesses, test scenarios, explaining attacks.
- Finding weak spots in code and configurations
- Reviewing incidents and explaining attack techniques
- Drafting scripts and procedures for the security team
- Sizes
- 7B – 70B
- 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
CodeOllama2024
INF Technology · China
Fully reproducible coding models: along with the weights, the data, its cleaning pipeline and the training recipe are open. Understand English and Chinese.
- Code generation and completion
- Training your own coding model from an open recipe
- A programming assistant on low-end hardware
- Sizes
- 1.5B – 8B
- Hardware
- from: Laptop
CodeOllama2023–2024
DeepSeek · China
DeepSeek's coding model family: from small autocompletion models to the large MoE V2, which matched closed models in 2024. Later, coding moved into DeepSeek's general models.
- Code autocompletion and generation
- Translating code between programming languages
- Finding bugs and explaining other people's code
- Sizes
- 1.3B – 236B-A21B
- 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
Tabular dataGGUF2024
RUCKBReasoning, Renmin University of China · China
A model for office work with tables: for a given question it returns either a direct answer or code to process the data in a table or document.
- Processing tables from Excel and documents from a text instruction
- Generating code for recalculations and selections
- Answering questions about data in reports
- Sizes
- 7B и 13B
- Hardware
- from: Laptop
TextOllamaNot maintained2023–2024
Stability AI · UK
Small models from Stability AI: StableLM 2 (1.6B) knows 7 European languages, Stable Code (3B) completes code. No updates since 2024.
- A lightweight chatbot on an ordinary PC
- Code autocompletion in the editor
- A base for fine-tuning on your own task
- Sizes
- 1.6B – 12B
- Hardware
- from: Laptop
CodeOllamaNot maintained2024
Mistral AI · France
Mistral's coding model covering 80+ programming languages. The open weights of the main version cannot be used in production without a paid license; newer Codestral versions are API-only.
- Evaluation and testing before buying a license
- Code autocompletion (with a commercial license)
- Research on coding model quality
- Sizes
- 7B – 22B
- Hardware
- from: Laptop
CodeOllamaNot maintained2023–2024
Zhipu AI (Z.ai) and Tsinghua University · China
Coding models from the creators of GLM. CodeGeeX4-ALL-9B, based on GLM-4-9B, combines autocompletion, code chat, function calling and repository search in one model.
- Code autocompletion in the IDE
- A code chat assistant
- Answering questions about a repository
- Sizes
- 6B – 9B
- Hardware
- from: Laptop
TextOllamaNot maintained2023–2024
OpenChat (Tsinghua University) · China
Fine-tunes of Mistral 7B and Llama 3 8B using the C-RLFT method that caught up with ChatGPT-3.5 in 2023–2024 at just 7–8B. A lightweight general-purpose assistant for a modest server.
- Chat assistant on an inexpensive server
- Drafts of emails and replies
- Help with simple code
- Sizes
- 7B – 13B
- 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
CodeOllamaNot maintained2023–2024
BigCode (Hugging Face and ServiceNow) · USA / France
One of the first open coding models, trained on an open set of source code with an option to exclude your own repository. Today it is more a base for fine-tuning than a leader.
- Code autocompletion in the editor
- Fine-tuning on the company's internal code
- Generating boilerplate code and tests
- Sizes
- 1B – 15B
- 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 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
CodeOllamaNot maintained2023–2024
Meta · USA
A version of Llama 2 further trained on code, with variants for Python and for chat. Outdated, but many ready-made fine-tuned versions and tools exist.
- Code autocompletion and explanation
- Generating Python scripts
- Base model for fine-tuning on your own stack
- Sizes
- 7B – 70B
- Hardware
- from: Laptop
TextOllamaNot maintained2023–2024
WizardLM (Microsoft and Peking University) · USA / China
Fine-tunes of Llama, Mistral and StarCoder using Evol-Instruct, which automatically makes instructions more complex. WizardLM-2 was released in April 2024 and removed almost immediately, so only the 2023 versions are relevant.
- Complex multi-step instructions
- Help for developers
- Solving math problems
- Sizes
- 7B – 70B
- Hardware
- from: Laptop
Text to SQLOllamaNot maintained2024
MotherDuck and Numbers Station · USA
A model for turning questions into SQL, built for the embedded analytics database DuckDB. Available in Ollama, convenient for working with CSV and Parquet locally.
- Plain-language questions about CSV and Parquet exports
- DuckDB queries inside analytics scripts
- Quick analytics on a laptop without a server
- Sizes
- 7B
- 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
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
