Model comparison
DeepSeek V4 Pro vs Mistral Medium 3.1
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 31.9 on the Noometry Index.
Last verified . 2 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 2 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 2 categories and Mistral Medium 3.1 in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 10.6.
- The biggest single-benchmark swing is NYT Connections (extended): 91.3% for DeepSeek V4 Pro and 6.5% for Mistral Medium 3.1.
- Mistral Medium 3.1 is cheaper at $0.40 / $2 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 131K.
- DeepSeek V4 Pro has downloadable open weights; the other is API-only.
Side by side
| DeepSeek V4 Pro | Mistral Medium 3.1 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 54.3 | 31.9 |
| Released | 2026-04-24 | — |
| Weights | Open | Proprietary |
| Context window | 1M | 131K |
| Max output | 393K | 105K |
| Input $ / M tokens | $0.66 | $0.40 |
| Output $ / M tokens | $1.98 | $2 |
| Results tracked | 48 | 3 |
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Category by category
Coding Not comparable
DeepSeek V4 Pro: 52.4 (#34), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| LMArena Coding | 1470 | — |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Pro: 32.8 (#58), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |
Reasoning DeepSeek V4 Pro leads
DeepSeek V4 Pro: 56.5 (#24), Mistral Medium 3.1: 10.6 (#341)
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| NYT Connections (extended) | 91.3% | 6.5% |
| ARC-AGI-2 | 61.3% | — |
| Kagi LLM Benchmark | 53.5% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| Thematic Generalization | — | 20.3% |
| LMArena Hard Prompts | 1461 | — |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.31 | — |
| ForecastBench | 56.1 | — |
Math Not comparable
DeepSeek V4 Pro: 64.8 (#30), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | — |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| OTIS Mock AIME 2024-2025 | 98.6% | — |
| ProofBench | 50% | — |
| LMArena Math | 1455 | — |
Knowledge Not comparable
DeepSeek V4 Pro: 59.5 (#31), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
| Vectara Hallucination Rate | 8.6% | — |
| LMArena Expert | 1464 | — |
Multilingual Not comparable
DeepSeek V4 Pro: 54.4 (#45), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| LMArena Non-English | 1439 | — |
| LMArena Chinese | 1486 | — |
| LMArena French | 1472 | — |
| LMArena German | 1458 | — |
| LMArena Japanese | 1445 | — |
| LMArena Korean | 1447 | — |
| LMArena Russian | 1453 | — |
| LMArena Spanish | 1458 | — |
Instruction Following Not comparable
DeepSeek V4 Pro: 76.1 (#47), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| LMArena Instruction Following | 1448 | — |
Long Context Not comparable
DeepSeek V4 Pro: 45.0 (#51), Mistral Medium 3.1: —
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| CL-bench Life | 13.5% | — |
| LMArena Longer Query | 1458 | — |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek V4 Pro: 65.5 (#46), Mistral Medium 3.1: 55.5 (#145)
| Benchmark | DeepSeek V4 Pro | Mistral Medium 3.1 |
|---|---|---|
| EQ-Bench Creative Writing | 1553 | 1476 |
| LMArena Text | 1451 | — |
| LMArena Creative Writing | 1446 | — |
| EQ-Bench 4 | 1166 | — |
| LMArena Multi-Turn | 1467 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than Mistral Medium 3.1?
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 31.9 on the Noometry Index.
Which is cheaper, DeepSeek V4 Pro or Mistral Medium 3.1?
Mistral Medium 3.1 is cheaper. It lists at $0.40 per million input tokens and $2 per million output tokens; DeepSeek V4 Pro lists at $0.66 and $1.98.
Which has the bigger context window?
DeepSeek V4 Pro does, with 1M tokens against 131K.
How many benchmarks do DeepSeek V4 Pro and Mistral Medium 3.1 share?
2 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Mistral Medium 3.1 has 3.