DeepSeek V4 vs Mistral Large
Pricing, benchmarks, and use case comparison
Quick take
- •DeepSeek V4 is meaningfully stronger at long context (97 vs 70 on our capability index).
- •Mistral Large is meaningfully stronger at multimodal (65 vs 10).
- •DeepSeek V4 is open-weights (free to self-host); Mistral Large is paid API only.
- •DeepSeek V4 has a 1M tokens context window vs 128000 - better for whole-repo or long-document work.
Specs comparison
| DeepSeek V4 | Mistral Large | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Type | Open source | Closed source |
| Context window | ✓1M tokens | 128000 |
| Input / 1M tokens | ✓Free (self-host) | 2.00 |
| Output / 1M tokens | Free (self-host) | 6.00 |
| Release date | 2026-04 | 2024-02 |
Benchmarks
| Benchmark | DeepSeek V4 | Mistral Large |
|---|---|---|
| SWE-bench Verified | 80.6% | - |
| Math / STEM / Coding (open-model comparison) | Best among open models (per DeepSeek) | - |
| MMLU | - | 84.0% |
| HumanEval | - | 92.0% |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose DeepSeek V4 if...
- →You need a frontier-class open model you can self-host for data control
- →Your workload involves very long documents, codebases, or agent trajectories (up to 1M tokens)
- →You want top-tier agentic coding at a fraction of closed-model cost
- →You need to fine-tune or customize a strong base model
Choose Mistral Large if...
- →You need a strong European-built flagship with open weights
- →Your work is multilingual or requires nuanced reasoning
- →You want structured/JSON output and solid coding ability
- →You need the option to self-host for data sovereignty