Model comparison
Claude Sonnet 4 vs Mistral Large 3
Claude Sonnet 4 is the stronger model overall, scoring 40.8 to 39.1 on the Noometry Index. Mistral Large 3 costs 16× less per token, which makes it the better buy when Claude Sonnet 4's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Mistral AISummary
- They share 21 benchmarks with published results for both. Claude Sonnet 4 scores higher in 4 categories and Mistral Large 3 in 5 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in multimodal, where Mistral Large 3 leads 38.2 to 26.2.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 73% for Claude Sonnet 4 and 50.9% for Mistral Large 3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.
- Mistral Large 3 accepts more context: 262K tokens versus 200K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4 | Mistral Large 3 | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 40.8 | 39.1 |
| Released | 2025-05-22 | 2025-12-02 |
| Weights | Proprietary | Open |
| Context window | 200K | 262K |
| Max output | 64K | 8K |
| Input $ / M tokens | $3 | $0.25 |
| Output $ / M tokens | $15 | $0.75 |
| Results tracked | 58 | 24 |
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Category by category
Coding Claude Sonnet 4 leads
Claude Sonnet 4: 43.5 (#88), Mistral Large 3: 34.4 (#237)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Coding | 1414 | 1448 |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| LMArena WebDev | — | 1230 |
| SciCode | 40% | — |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
| ALE-Bench | 655.35 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4: 38.5 (#31), Mistral Large 3: —
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |
Reasoning Claude Sonnet 4 leads
Claude Sonnet 4: 22.9 (#187), Mistral Large 3: 15.2 (#319)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 73% | 50.9% |
| LMArena Hard Prompts | 1372 | 1429 |
| ARC-AGI-2 | 5.9% | — |
| SimpleBench | 45.5% | — |
| NYT Connections (extended) | — | 7.5% |
| ARC-AGI-1 | 40% | — |
| CritPt | 0.3% | — |
| EnigmaEval | 3.1% | — |
| Thematic Generalization | — | 23% |
| DTBench | 77.1% | — |
| LMCA | 29% | — |
| Epoch Capabilities Index | 141.69 | — |
| ForecastBench | 60.2 | — |
Math Claude Sonnet 4 leads
Claude Sonnet 4: 43.3 (#80), Mistral Large 3: 38.7 (#129)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1375 | 1414 |
| OTIS Mock AIME 2024-2025 | 71.1% | — |
| Omni-MATH | 60.2% | — |
| MATH Level 5 | 84.4% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Claude Sonnet 4 leads
Claude Sonnet 4: 41.8 (#108), Mistral Large 3: 36.0 (#177)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 10.3% | 14.5% |
| LMArena Expert | 1372 | 1421 |
| GPQA Diamond | 79.2% | — |
| Humanity's Last Exam | 7.8% | — |
| MMLU-Pro | 84.3% | — |
| Confabulations | 13.2% | — |
| GPQA (HELM) | 70.6% | — |
Multimodal Mistral Large 3 leads
Claude Sonnet 4: 26.2 (#121), Mistral Large 3: 38.2 (#66)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1191 | 1221 |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |
Multilingual Mistral Large 3 leads
Claude Sonnet 4: 46.7 (#156), Mistral Large 3: 52.5 (#84)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1333 | 1413 |
| LMArena Chinese | 1350 | 1447 |
| LMArena French | 1363 | 1455 |
| LMArena German | 1331 | 1437 |
| LMArena Japanese | 1302 | 1394 |
| LMArena Korean | 1291 | 1384 |
| LMArena Russian | 1355 | 1411 |
| LMArena Spanish | 1357 | 1440 |
Instruction Following Mistral Large 3 leads
Claude Sonnet 4: 71.7 (#145), Mistral Large 3: 74.0 (#108)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1376 | 1403 |
| IFEval | 84% | — |
Long Context Mistral Large 3 leads
Claude Sonnet 4: 33.7 (#259), Mistral Large 3: 43.1 (#105)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1398 | 1413 |
| Fiction.LiveBench | 46.9% | — |
Writing & Preference Mistral Large 3 leads
Claude Sonnet 4: 57.1 (#132), Mistral Large 3: 60.0 (#101)
| Benchmark | Claude Sonnet 4 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1351 | 1428 |
| LMArena Creative Writing | 1345 | 1386 |
| EQ-Bench Creative Writing | 1483 | 1412 |
| LMArena Multi-Turn | 1376 | 1429 |
| Short-Story Creative Writing | 81.4% | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is Claude Sonnet 4 better than Mistral Large 3?
Claude Sonnet 4 is the stronger model overall, scoring 40.8 to 39.1 on the Noometry Index. Mistral Large 3 costs 16× less per token, which makes it the better buy when Claude Sonnet 4's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 4 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; Claude Sonnet 4 lists at $3 and $15.
Is Claude Sonnet 4 or Mistral Large 3 better for coding?
Claude Sonnet 4 scores higher on coding benchmarks: 43.5 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Mistral Large 3 does, with 262K tokens against 200K.
How many benchmarks do Claude Sonnet 4 and Mistral Large 3 share?
21 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and Mistral Large 3 has 24.