DeepSeek-Coder-V2: First Open Source Coding Model Beats GPT4-Turbo

DeepSeek-Coder-V2 is an open-source coding model developed by DeepSeek AI, surpassing models like GPT4-Turbo in performance thanks to its 236 billion parameter architecture trained on 6 trillion tokens. The model supports over 338 programming languages, excels in coding tasks, and incorporates advanced training techniques like supervised fine-tuning and reinforcement learning for accurate and tailored responses.

DeepSeek-Coder-V2 is an open-source coding model developed by DeepSeek AI that has been trained on an additional 6 trillion tokens to improve its performance. This new version of the model is considered to be one of the most impressive large language models to come out of China, excelling not only in coding tasks but also in general language understanding. Benchmark tests have shown that DeepSeek-Coder-V2 is outperforming other models such as GPT4-Turbo, Cloud 3 Opus Gemini 1, and Codestrol from Mistol AI.

The model is based on a 236 billion parameter mixture of experts architecture, with 21 billion active parameters at any given time. It supports over 338 programming languages and has an extended context length of 128,000 tokens compared to the previous version. DeepSeek AI focused on finding additional tokens for training and utilized pre-training techniques to optimize the model’s performance. The additional tokens included raw source code, math corpus, and natural language corpus sourced from GitHub and Common Crawl.

To further enhance the model’s performance, DeepSeek AI implemented supervised fine-tuning on code data and general instruction data, followed by reinforcement learning using Group Relative Policy Optimization (GRPO). The model’s responses were optimized for correctness and human preference on coding tasks, incorporating test case feedback and a learned reward model. The use of test case feedback and a learned reward model sets DeepSeek-Coder-V2 apart from other models, allowing for more accurate and tailored responses in coding tasks.

DeepSeek-Coder-V2 is available on Hugging Face and DeepSeek AI GitHub, offering two versions of the API with different parameter sizes. The model has been trained on a diverse range of programming languages, including older and more specialized languages like AMD GPU, Ambient Talk, and VHDL. Users can interact with the model by providing coding instructions and tasks, and it demonstrates a strong ability to generate well-written code snippets and understand complex programming concepts like building ASICs for Bitcoin mining.

Overall, DeepSeek-Coder-V2 showcases significant advancements in the field of large language models, particularly in the domain of coding tasks. Its enhanced performance, support for a wide range of programming languages, and sophisticated training techniques make it a valuable tool for developers and engineers. The model’s ability to generate code, provide explanations, and handle complex tasks like ASIC design demonstrates its versatility and potential for various applications in software development and programming.