DeepSeek Coder 2 defeats the open source GPT4-Turbo coding model

DeepSeek-Coder-V2, developed by DeepSeek AI, represents a significant advancement in Large Language Models (LLM) for coding. It outperforms other outstanding models such as GPT-4 Turbo, Cloud 3, Opus Gemini 1 and Codestrol in coding and math tasks. DeepSeek-Coder-V2 offers an impressive mixture of 236 billion expert model parameters, with 21 billion active parameters at any time. This extensive parameterization allows the model to easily address complex coding challenges. Moreover, the model supports an astonishing 338 programming languages, making it an invaluable asset for developers working with a variety of code bases, including legacy and exotic languages.

DeepSeek-Coder-V2

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

These results highlight DeepSeek-Coder-V2’s unique ability to solve complex coding and mathematical problems, making it an essential tool for software engineers looking to streamline their workflow and increase productivity.

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Intensive training and tuning

The secret to DeepSeek-Coder-V2’s unmatched performance lies in its comprehensive training and pre-training enhancements. The model was trained on an additional 6 trillion tokens based on a diverse dataset including:

• 60% raw source code
• 10% of the mathematics corpus
• 30% of the natural language corpus

This extensive training is further enhanced by supervised tuning of code and general instruction data, making the model well-equipped to handle a wide range of tasks. Additionally, DeepSeek-Coder-V2 undergoes reinforcement learning using Group Relative Policy Optimization (GRPO), which further improves its capabilities.

## Versatile possibilities and practical applications

DeepSeek-Coder-V2 excels not only in complex coding tasks, but also in simplifying code and efficiently handling non-coding tasks. The model’s proficiency in languages ​​such as Python AND VHDL shows its versatility and makes it an invaluable tool for developers working on a variety of projects. The model is available in two variants:

• Version with 230 billion parameters
• A smaller version with 16 billion parameters

Both versions include walkthrough and chat features, increasing their usability and enabling 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 available to the developer community via the Hugging Face and DeepSeek AI GitHub repository. This accessibility encourages community use, feedback and collaboration, creating 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 technologies, benefiting from the collective knowledge and experience of the developer community. As more developers adopt and contribute to this model, it will have 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 unmatched performance, broad language support, and versatile capabilities, this model has the potential to change the way software engineers approach coding tasks.

By harnessing the power of DeepSeek-Coder-V2, developers can streamline their workflows, solve complex challenges, and unlock new opportunities in software development. As the model evolves through collaboration and community feedback, it has the potential to shape the future of coding assistance and empower developers around the world.

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