Awesome-Code-LLM
👨💻 An awesome and curated list of best code-LLM for research.
GraphCanon updated 2w · GitHub synced 2w
Decision brief
Awesome-Code-LLM is a curated repository focused on code-focused large language models (code-LLMs), providing insights into top-performing models, evaluation toolkits, and research papers.
Good fit when
- When you need a comprehensive list of state-of-the-art code generation LLMs with performance metrics such as HumanEval.
- If you are conducting or contributing to research in the area of code-LLMs and want access to recent model releases like Qwen2.5-Coder series.
Avoid when
- When looking for a tool that provides pre-trained models with built-in APIs or services, as Awesome-Code-LLM is primarily a directory/collection of information without direct service provision.
- If you require real-time interactive use-cases and need immediate API access to LLMs; this repository does not offer such functionality.
- Requirements:
- No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs.
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (604d since push)
- As of 2w
- Provenance
- Not a fork · Personal account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/huybery/Awesome-Code-LLMSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A curated list of the best large language models (LLMs) focused on code generation, including top models, evaluation toolkits, and relevant papers.
Capability facts
No sourced capability facts yet. Facts appear after ingest scans repo manifests (Dockerfile, package.json, MCP configs).
Categories
Tags
README
👨💻 Awesome Code LLM
🔆 How to Contribute
Contributions are welcome! If you have any resources, tools, papers, or insights related to Code LLMs, feel free to submit a pull request. Let's work together to make this project better!
News
- 🔥🔥🔥 [2024-11-12] Qwen2.5-Coder series are released, offering six model sizes (0.5B, 1.5B, 3B, 7B, 14B, 32B), with Qwen2.5-Coder-32B-Instruct now the most powerful open-source code model.
- 🔥🔥 [2024-11-08] OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models is released.
🧵 Table of Contents
- 🧵 Table of Contents
- 🚀 Top Code LLMs
- 💡 Evaluation Toolkit
- 🚀 Awesome Code LLMs Leaderboard
- 📚 Awesome Code LLMs Papers
- 🌊 Awesome Code Pre-Training Papers
- 🐳 Awesome Code Instruction-Tuning Papers
- 🐬 Awesome Code Alignment Papers
- 🐋 Awesome Code Prompting Papers
- 🐙 Awesome Code Benchmark & Evaluation Papers
- 🙌 Contributors
- Cite as
- Acknowledgement
- Star History
🚀 Top Code LLMs
Sort by HumanEval Pass@1
| Rank | Model | Params | HumanEval | MBPP | Source |
|---|---|---|---|---|---|
| 1 | o1-mini-2024-09-12 | - | 97.6 | 93.9 | paper |
| 2 | o1-preview-2024-09-12 | - | 95.1 | 93.4 | paper |
| 3 | Qwen2.5-Coder-32B-Instruct | 32B | 92.7 | 90.2 | github |
| 4 | Claude-3.5-Sonnet-20241022 | - | 92.1 | 91.0 | paper |
| 5 | GPT-4o-2024-08-06 | - | 92.1 | 86.8 | paper |
| 6 | Qwen2.5-Coder-14B-Instruct | 14B | 89.6 | 86.2 | github |
| 7 | Claude-3.5-Sonnet-20240620 | - | 89.0 | 87.6 | paper |
| 8 | GPT-4o-mini-2024-07-18 | - | 87.8 | 86.0 | [paper](https://arxi |
For agents
This page has a .md twin and JSON over the API.