Curiosity · AI Model
DeepSeek Coder V2
DeepSeek Coder V2 is DeepSeek's mid-2024 code-specialized open-weights MoE — 236B total parameters with 21B active per token, fine-tuned on 6T additional code tokens. At release it matched GPT-4 Turbo on HumanEval and MBPP while remaining fully open, making it the go-to base for self-hosted coding copilots.
Model specs
- Vendor
- DeepSeek
- Family
- DeepSeek Coder
- Released
- 2024-06
- Context window
- 128,000 tokens
- Modalities
- text, code
- Input price
- $0.14/M tok
- Output price
- $0.28/M tok
- Pricing as of
- 2026-04-20
Strengths
- Open weights under MIT-compatible DeepSeek license
- GPT-4 Turbo class code quality at open-source inference cost
- MoE architecture — only 21B active per token means strong latency
- Supports 338 programming languages in pretraining data
Limitations
- Surpassed on pure HumanEval by Qwen 2.5 Coder 32B in late 2024
- 236B total footprint still demands multi-GPU hosting in BF16
- Limited tool-use and agentic fine-tuning versus Claude / GPT-5
- Less mature IDE integration than Codestral's fill-in-the-middle
Use cases
- Self-hosted IDE and terminal coding copilots
- Repository-scale code generation with 128K context
- Educational coding assistants in resource-constrained environments
- Base model for fine-tuning language-specific coding assistants
Benchmarks
| Benchmark | Score | As of |
|---|---|---|
| HumanEval | ≈90% | 2024-06 |
| MBPP | ≈77% | 2024-06 |
| LiveCodeBench | ≈44% | 2024-06 |
Frequently asked questions
Is DeepSeek Coder V2 still the best open coder?
As of April 2026 it's competitive with Qwen 2.5 Coder 32B and a generation ahead of Code Llama. Qwen often wins on HumanEval; DeepSeek Coder V2 wins on broader multi-language coverage and longer context handling.
What languages does DeepSeek Coder V2 support?
The pretraining corpus covers 338 programming languages. Practical quality is strongest in Python, JavaScript, TypeScript, Java, C++, Go, Rust, and SQL.
Is there a smaller DeepSeek Coder V2?
Yes — DeepSeek Coder V2 Lite ships at 16B total / 2.4B active, suitable for single-GPU inference while retaining strong code generation quality.
Sources
- DeepSeek — DeepSeek Coder V2 — accessed 2026-04-20
- Hugging Face — deepseek-ai/DeepSeek-Coder-V2-Instruct — accessed 2026-04-20