DeepSeek-Coder-V2 is the version-2 iteration of DeepSeek’s code generation models, refining the original DeepSeek-Coder line with improved architecture, training strategies, and benchmark performance. While the V1 models already targeted strong code understanding and generation, V2 appears to push further in both multilingual support and reasoning in code, likely via architectural enhancements or additional training objectives. The repository provides updated model weights, evaluation results on benchmarks (e.g. HumanEval, MultiPL-E, APPS), and new inference/serving scripts. Compared to the original, DeepSeek-Coder-V2 likely incorporates improved context management, caching strategies, or enhanced infilling capabilities. The project aims to provide a more performant and reliable open-source alternative to closed-source code models, optimized for practical usage in code completion, infilling, and code understanding across English and Chinese codebases.

Features

  • New model iteration with architectural or training improvements over DeepSeek-Coder V1
  • Updated model weights and inference / serving scripts
  • Enhanced performance on code benchmarks (HumanEval, MultiPL-E, APPS, etc)
  • Better multilingual and cross-context code generation (English + Chinese)
  • Improved infilling, context management, and code reasoning capabilities
  • Permissive license and encouragement for community use and extension

Project Samples

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Categories

AI Models

License

MIT License

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Registered

2025-10-03