DeepSeek Coder 2 beats GPT4-Turbo open source coding model

DeepSeek-Coder-V2, developed by DeepSeek AI, is a significant advancement in large language models (LLMs) for coding. It surpasses other prominent models like GPT-4 Turbo, Cloud 3, Opus Gemini 1, and Codestrol in coding and mathematical tasks. DeepSeek-Coder-V2 features an impressive 236 billion parameter mixture of experts model, with 21 billion active parameters at any given time. This extensive parameterization allows the model to tackle complex coding challenges with ease. Moreover, the model supports an astounding 338 programming languages, making it an invaluable asset for developers working with diverse codebases, including older and exotic languages.

DeepSeek-Coder-V2

The model’s superior performance is evident in its outstanding results in coding and math benchmarks. DeepSeek-Coder-V2 consistently outperforms its competitors, including GPT-4 Turbo, by a significant margin in benchmarks such as: GSM 8K, MB Plus+ and sbench.

These results underscore DeepSeek-Coder-V2’s exceptional ability to tackle complex coding and mathematical problems, making it an indispensable tool for software engineers seeking to streamline their workflows and boost productivity.

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Extensive Training and Fine-Tuning

The secret behind DeepSeek-Coder-V2’s unrivaled performance lies in its comprehensive training and pre-training enhancements. The model has been trained on an additional 6 trillion tokens, drawing from a diverse dataset comprising:

• 60% raw source code
• 10% math corpus
• 30% natural language corpus

This extensive training is further bolstered by supervised fine-tuning on code and general instruction data, ensuring that the model is well-equipped to handle a wide range of tasks. Additionally, DeepSeek-Coder-V2 undergoes reinforcement learning using group relative policy optimization (GRPO), further refining its capabilities.

## Versatile Capabilities and Practical Applications

DeepSeek-Coder-V2 excels not only in complex coding tasks but also in simplifying code and handling non-programming tasks effectively. The model’s proficiency in languages such as Python and VHDL showcases its versatility and makes it an invaluable tool for developers working on diverse projects. The model is available in two variants:

• A 230 billion parameter version
• A smaller 16 billion parameter version

Both versions include instruct and chat functionalities, enhancing their usability and allowing for seamless interaction with users. These features enable the model to provide detailed instructions and engage in meaningful conversations, further streamlining the coding process.

Empowering the Developer Community

As an open source model, DeepSeek-Coder-V2 is readily accessible to the developer community through Hugging Face and DeepSeek AI’s GitHub repository. This accessibility encourages community use, feedback, and collaboration, fostering an environment of continuous improvement and innovation.

The open source nature of DeepSeek-Coder-V2 ensures that the model remains at the forefront of coding assistance technology, benefiting from the collective knowledge and expertise of the developer community. As more developers adopt and contribute to the model, it has the potential to evolve and adapt to the ever-changing needs of the software engineering landscape.

DeepSeek-Coder-V2 represents a significant milestone in the evolution of open source coding models. With its unparalleled performance, extensive language support, and versatile capabilities, this model is poised to transform the way software engineers approach coding tasks.

By harnessing the power of DeepSeek-Coder-V2, developers can streamline their workflows, tackle complex challenges, and unlock new possibilities in software development. As the model continues to evolve through community collaboration and feedback, it has the potential to shape the future of coding assistance and empower developers worldwide.

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