DeepSeek-Coder-v2-16|236B-MOE
FreeBreaking the Barrier of Closed-Source Models in Code Intelligence
FreeFree tier
Inputs: code, textOutputs: code, text
About DeepSeek-Coder-v2-16|236B-MOE
DeepSeek-Coder-V2 is an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT-4 Turbo in code-specific tasks. It is further pre-trained from an intermediate checkpoint of DeepSeek-V2 with an additional 6 trillion tokens, enhancing coding and mathematical reasoning capabilities while maintaining general language performance. The model supports 338 programming languages (up from 86) and extends context length from 16K to 128K. It is available in 16B and 236B parameter versions (with 2.4B and 21B active parameters respectively), including base and instruct variants, downloadable from HuggingFace.
Key Features
Mixture-of-Experts (MoE) architecture with 16B and 236B total parameters (2.4B and 21B active)
Supports 338 programming languages
Extended context length of 128K tokens
Pre-trained on additional 6 trillion tokens from DeepSeek-V2 checkpoint
Outperforms GPT-4 Turbo, Claude 3 Opus, and Gemini 1.5 Pro on coding and math benchmarks
Available as base and instruct models on HuggingFace
Pros & Cons
Pros
- Open-source with public model weights
- State-of-the-art performance on code benchmarks comparable to leading closed-source models
- Supports a vast number of programming languages (338)
- Long context window (128K) for handling large codebases
- Efficient MoE design reduces active parameters
Cons
- Larger model variants (236B) require significant computational resources
- No official API or cloud service provided; models must be self-hosted
Best For
Code generation and completionCode fixing and debuggingMathematical reasoningGeneral language tasksOpen-source code intelligence research
FAQ
What model sizes are available for DeepSeek-Coder-V2?
DeepSeek-Coder-V2 comes in two sizes: a 16B total parameter version with 2.4B active parameters (Lite) and a 236B total parameter version with 21B active parameters. Both have base and instruct variants.
How does DeepSeek-Coder-V2 compare to GPT-4 Turbo?
According to the benchmarks, DeepSeek-Coder-V2-Instruct achieves a HumanEval score of 90.2% and MBPP+ of 76.2%, outperforming GPT-4 Turbo (87.8% and 69.3% respectively) and other closed-source models like Claude 3 Opus and Gemini 1.5 Pro in code generation tasks.
What programming languages does DeepSeek-Coder-V2 support?
DeepSeek-Coder-V2 supports 338 programming languages, expanded from the 86 supported by its predecessor DeepSeek-Coder-33B.
How can I download and use DeepSeek-Coder-V2?
The models are available for download on HuggingFace under the 'deepseek-ai' organization. Both base and instruct models for the 16B and 236B variants can be accessed.