Model comparison
DeepSeek V4 Pro vs Mistral Large 3
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 39.1 on the Noometry Index. Mistral Large 3 costs 2.6× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
DeepSeek
Mistral AISummary
- They share 22 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 8 categories and Mistral Large 3 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 15.2.
- The biggest single-benchmark swing is NYT Connections (extended): 91.3% for DeepSeek V4 Pro and 7.5% for Mistral Large 3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.66 / $1.98 for DeepSeek V4 Pro.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 262K.
Side by side
| DeepSeek V4 Pro | Mistral Large 3 | |
|---|---|---|
| Provider | DeepSeek | Mistral AI |
| Noometry Index | 54.3 | 39.1 |
| Released | 2026-04-24 | 2025-12-02 |
| Weights | Open | Open |
| Context window | 1M | 262K |
| Max output | 393K | 8K |
| Input $ / M tokens | $0.66 | $0.25 |
| Output $ / M tokens | $1.98 | $0.75 |
| Results tracked | 48 | 24 |
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Category by category
Coding DeepSeek V4 Pro leads
DeepSeek V4 Pro: 52.4 (#34), Mistral Large 3: 34.4 (#237)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1582 | 1230 |
| LMArena Coding | 1470 | 1448 |
| SWE-bench Verified | 77.6% | — |
| FrontierCode | 28.6% | — |
| SciCode | 51% | — |
| WeirdML | 66.2% | — |
| ALE-Bench | 1,403 | — |
Agentic & Tool Use Not comparable
DeepSeek V4 Pro: 32.8 (#58), Mistral Large 3: —
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Vending-Bench 2 | 3,285 | — |
Reasoning DeepSeek V4 Pro leads
DeepSeek V4 Pro: 56.5 (#24), Mistral Large 3: 15.2 (#319)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 53.5% | 50.9% |
| NYT Connections (extended) | 91.3% | 7.5% |
| LMArena Hard Prompts | 1461 | 1429 |
| ARC-AGI-2 | 61.3% | — |
| ARC-AGI-1 | 90.5% | — |
| CritPt | 18% | — |
| Chess Puzzles | 47% | — |
| Thematic Generalization | — | 23% |
| Mystery Game Puzzles | 43% | — |
| DTBench | 93.9% | — |
| LMCA | 45.5% | — |
| Surface Evolver Bench | 40% | — |
| Epoch Capabilities Index | 155.31 | — |
| ForecastBench | 56.1 | — |
Math DeepSeek V4 Pro leads
DeepSeek V4 Pro: 64.8 (#30), Mistral Large 3: 38.7 (#129)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1455 | 1414 |
| 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% | — |
Knowledge DeepSeek V4 Pro leads
DeepSeek V4 Pro: 59.5 (#31), Mistral Large 3: 36.0 (#177)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 8.6% | 14.5% |
| LMArena Expert | 1464 | 1421 |
| GPQA Diamond | 91.7% | — |
| SimpleQA Verified | 52.9% | — |
Multimodal Not comparable
DeepSeek V4 Pro: —, Mistral Large 3: 38.2 (#66)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena Vision | — | 1221 |
Multilingual DeepSeek V4 Pro leads
DeepSeek V4 Pro: 54.4 (#45), Mistral Large 3: 52.5 (#84)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1439 | 1413 |
| LMArena Chinese | 1486 | 1447 |
| LMArena French | 1472 | 1455 |
| LMArena German | 1458 | 1437 |
| LMArena Japanese | 1445 | 1394 |
| LMArena Korean | 1447 | 1384 |
| LMArena Russian | 1453 | 1411 |
| LMArena Spanish | 1458 | 1440 |
Instruction Following DeepSeek V4 Pro leads
DeepSeek V4 Pro: 76.1 (#47), Mistral Large 3: 74.0 (#108)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1448 | 1403 |
Long Context DeepSeek V4 Pro leads
DeepSeek V4 Pro: 45.0 (#51), Mistral Large 3: 43.1 (#105)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1458 | 1413 |
| CL-bench Life | 13.5% | — |
Writing & Preference DeepSeek V4 Pro leads
DeepSeek V4 Pro: 65.5 (#46), Mistral Large 3: 60.0 (#101)
| Benchmark | DeepSeek V4 Pro | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1451 | 1428 |
| LMArena Creative Writing | 1446 | 1386 |
| EQ-Bench Creative Writing | 1553 | 1412 |
| LMArena Multi-Turn | 1467 | 1429 |
| EQ-Bench 4 | 1166 | — |
Frequently asked questions
Is DeepSeek V4 Pro better than Mistral Large 3?
DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 39.1 on the Noometry Index. Mistral Large 3 costs 2.6× less per token, which makes it the better buy when DeepSeek V4 Pro's lead doesn't matter for your workload.
Which is cheaper, DeepSeek V4 Pro or Mistral Large 3?
Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; DeepSeek V4 Pro lists at $0.66 and $1.98.
Is DeepSeek V4 Pro or Mistral Large 3 better for coding?
DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
DeepSeek V4 Pro does, with 1M tokens against 262K.
How many benchmarks do DeepSeek V4 Pro and Mistral Large 3 share?
22 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and Mistral Large 3 has 24.