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DeepSeek-Coder-V2

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description DeepSeek-Coder-V2 Overview

DeepSeek-Coder-V2 is an open-weights language model designed for advanced code generation. Developed by Continue.AI, it leverages a CodeGen-UvLM architecture and incorporates Mixture of Experts (MoE) technology to improve performance. This model is particularly useful for developers, software engineers, and AI tool creators requiring robust code understanding and generation capabilities within coding assistants or IDE environments.

help DeepSeek-Coder-V2 FAQ

Who developed DeepSeek-Coder-V2?

DeepSeek-Coder-V2 was developed by DeepSeek, not Continue.AI. Continue can use many coding models inside an IDE, but the model family itself comes from DeepSeek.

What is DeepSeek-Coder-V2 built for?

It is built for code generation, code completion, repository understanding, and general reasoning around programming tasks. Developers often compare it with models such as Code Llama, Qwen Coder, and StarCoder2.

Why do people mention 236B and 21B with DeepSeek-Coder-V2?

DeepSeek's V2 architecture is a mixture-of-experts design, so the total parameter count and the active parameters per token are different. Public DeepSeek-V2 material described 236 billion total parameters with about 21 billion active per token.

Can DeepSeek-Coder-V2 run locally?

Some DeepSeek-Coder-V2 variants and quantized releases can be run locally by advanced users, but hardware needs depend heavily on the model size and quantization. Many people instead use it through hosted APIs or IDE integrations because full-size models need serious GPU memory.

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