{"data":{"slug":"huybery-awesome-code-llm","name":"Awesome-Code-LLM","tagline":"๐Ÿ‘จ๐Ÿ’ป An awesome and curated list of best code-LLM for research.","github_url":"https://github.com/huybery/Awesome-Code-LLM","owner":"huybery","repo":"Awesome-Code-LLM","owner_avatar_url":"https://avatars.githubusercontent.com/u/13436140?v=4","primary_language":null,"stars":1288,"forks":74,"topics":["awesome","code-generation","large-language-models"],"archived":false,"github_pushed_at":"2024-12-10T08:10:54+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/huybery-awesome-code-llm","markdown_url":"https://www.graphcanon.com/tools/huybery-awesome-code-llm.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/huybery-awesome-code-llm","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=huybery-awesome-code-llm","description":"๐Ÿ‘จโ€๐Ÿ’ป An awesome and curated list of best code-LLM for research.","homepage_url":null,"license":"MIT","open_issues":3,"watchers":33,"ai_summary":"A curated list of the best large language models (LLMs) focused on code generation, including top models, evaluation toolkits, and relevant papers.","readme_excerpt":"
\n

๐Ÿ‘จโ€๐Ÿ’ป Awesome Code LLM

\n \n \"Awesome\"\n \n \n \"PRs\n \n \n \"Last\n \n
\n\n\n\n \n\n## ๐Ÿ”† How to Contribute\n\nContributions are welcome!\nIf you have any resources, tools, papers, or insights related to Code LLMs, feel free to submit a pull request.\nLet's work together to make this project better!\n\n \n\n## News\n\n- ๐Ÿ”ฅ๐Ÿ”ฅ๐Ÿ”ฅ **[2024-11-12]** [**Qwen2.5-Coder series**](https://huggingface.co/collections/Qwen/qwen25-66e81a666513e518adb90d9e) 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.\n- ๐Ÿ”ฅ๐Ÿ”ฅ **[2024-11-08]** [OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://arxiv.org/abs/2411.04905) is released.\n\n \n\n## ๐Ÿงต Table of Contents\n\n- [๐Ÿงต Table of Contents](#-table-of-contents)\n- [๐Ÿš€ Top Code LLMs](#-top-code-llms)\n- [๐Ÿ’ก Evaluation Toolkit](#-evaluation-toolkit)\n- [๐Ÿš€ Awesome Code LLMs Leaderboard](#-awesome-code-llms-leaderboard)\n- [๐Ÿ“š Awesome Code LLMs Papers](#-awesome-code-llms-papers)\n - [๐ŸŒŠ Awesome Code Pre-Training Papers](#-awesome-code-pre-training-papers)\n - [๐Ÿณ Awesome Code Instruction-Tuning Papers](#-awesome-code-instruction-tuning-papers)\n - [๐Ÿฌ Awesome Code Alignment Papers](#-awesome-code-alignment-papers)\n - [๐Ÿ‹ Awesome Code Prompting Papers](#-awesome-code-prompting-papers)\n - [๐Ÿ™ Awesome Code Benchmark \\& Evaluation Papers](#-awesome-code-benchmark--evaluation-papers)\n- [๐Ÿ™Œ Contributors](#-contributors)\n- [Cite as](#cite-as)\n- [Acknowledgement](#acknowledgement)\n- [Star History](#star-history)\n\n \n\n## ๐Ÿš€ Top Code LLMs\n###### Sort by HumanEval Pass@1\n\n| Rank | Model | Params | HumanEval | MBPP | Source |\n|------|-------------------------------------------------------------------------------------------------|---------|-----------|------|------------------------------------------------------------|\n| 1 | o1-mini-2024-09-12 | - | 97.6 | 93.9 | [paper](https://arxiv.org/abs/2409.12186) |\n| 2 | o1-preview-2024-09-12 | - | 95.1 | 93.4 | [paper](https://arxiv.org/abs/2409.12186) |\n| 3 | [Qwen2.5-Coder-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-32B-Instruct) | 32B | 92.7 | 90.2 | [github](https://github.com/QwenLM/Qwen2.5-Coder) |\n| 4 | Claude-3.5-Sonnet-20241022 | - | 92.1 | 91.0 | [paper](https://arxiv.org/abs/2409.12186) |\n| 5 | GPT-4o-2024-08-06 | - | 92.1 | 86.8 | [paper](https://arxiv.org/abs/2409.12186) |\n| 6 | [Qwen2.5-Coder-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-14B-Instruct) | 14B | 89.6 | 86.2 | [github](https://github.com/QwenLM/Qwen2.5-Coder) |\n| 7 | Claude-3.5-Sonnet-20240620 | - | 89.0 | 87.6 | [paper](https://arxiv.org/abs/2409.12186) |\n| 8 | GPT-4o-mini-2024-07-18 | - | 87.8 | 86.0 | [paper](https://arxi","github_created_at":"2023-07-05T06:42:09+00:00","created_at":"2026-07-11T10:32:37.03217+00:00","updated_at":"2026-07-11T11:21:40.913358+00:00","categories":[{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"awesome","name":"awesome"},{"slug":"large-language-models","name":"large-language-models"},{"slug":"code-generation","name":"code-generation"}],"trust":{"provenance":{"is_fork":false,"github_id":662443651,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T10:32:37.618Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":578,"last_release_at":null},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T10:32:38.247Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T11:20:56.347Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-11T11:20:56.347Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs."]},"constraints":null,"when_to_use":["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.","For evaluation purposes, when needing specific toolkits for benchmarking and assessing the capabilities of different models."],"when_not_to_use":["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.","In scenarios where you need a single end-to-end solution for training your own code generation models, as the platform is focused on aggregating third-party resources and research rather than offering"],"source":"enrich:decision_facts","observed_at":"2026-07-11T11:21:40.633Z"},"constraint_facets":null,"decision_summary":[{"label":"Requirements","value":"No specific requirements to use the repository for reference or evaluation, but contributions may involve technical knowledge and familiarity with code-LLMs."},{"label":"Adopt for","value":"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."},{"label":"License detail","value":"MIT License: Permissive open-source license that allows usage in virtually any project with little restrictions."}]}}