Model comparison
Claude Sonnet 4.6 vs Mistral Large 3
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 39.1 on the Noometry Index. Mistral Large 3 costs 16× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Mistral AISummary
- They share 23 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 8 categories and Mistral Large 3 in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Sonnet 4.6 leads 46.1 to 15.2.
- The biggest single-benchmark swing is NYT Connections (extended): 80.9% for Claude Sonnet 4.6 and 7.5% 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 4.6.
- Claude Sonnet 4.6 accepts more context: 1M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4.6 | Mistral Large 3 | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 50.3 | 39.1 |
| Released | 2026-02-17 | 2025-12-02 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 128K | 8K |
| Input $ / M tokens | $3 | $0.25 |
| Output $ / M tokens | $15 | $0.75 |
| Results tracked | 57 | 24 |
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Category by category
Coding Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.3 (#67), Mistral Large 3: 34.4 (#237)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1522 | 1230 |
| LMArena Coding | 1504 | 1448 |
| SWE-bench Verified | 75.2% | — |
| DeepSWE | 29.9% | — |
| FrontierCode | 24.3% | — |
| SciCode | 46.8% | — |
| WeirdML | 66.1% | — |
| ALE-Bench | 1,327 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4.6: 39.1 (#28), Mistral Large 3: —
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| Terminal-Bench | 53.4% | — |
| APEX-Agents | 43% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| GDP.pdf | 18% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#45), Mistral Large 3: 15.2 (#319)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| NYT Connections (extended) | 80.9% | 7.5% |
| Thematic Generalization | 76.3% | 23% |
| LMArena Hard Prompts | 1484 | 1429 |
| ARC-AGI-2 | 60.4% | — |
| Kagi LLM Benchmark | — | 50.9% |
| ARC-AGI-1 | 86.5% | — |
| CritPt | 3.1% | — |
| Chess Puzzles | 13% | — |
| Mystery Game Puzzles | 16% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| Epoch Capabilities Index | 152.24 | — |
| ForecastBench | 62 | — |
Math Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 52.9 (#49), Mistral Large 3: 38.7 (#129)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1462 | 1414 |
| OTIS Mock AIME 2024-2025 | 85.8% | — |
| ProofBench | 45% | — |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
Knowledge Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 51.7 (#65), Mistral Large 3: 36.0 (#177)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 10.6% | 14.5% |
| LMArena Expert | 1500 | 1421 |
| GPQA Diamond | 87.4% | — |
| SimpleQA Verified | 35.5% | — |
Multimodal Too close to call
Claude Sonnet 4.6: 38.0 (#68), Mistral Large 3: 38.2 (#66)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1283 | 1221 |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 54.4 (#41), Mistral Large 3: 52.5 (#84)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1440 | 1413 |
| LMArena Chinese | 1491 | 1447 |
| LMArena French | 1465 | 1455 |
| LMArena German | 1428 | 1437 |
| LMArena Japanese | 1420 | 1394 |
| LMArena Korean | 1411 | 1384 |
| LMArena Russian | 1440 | 1411 |
| LMArena Spanish | 1464 | 1440 |
Instruction Following Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 77.4 (#25), Mistral Large 3: 74.0 (#108)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1475 | 1403 |
Long Context Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 45.3 (#44), Mistral Large 3: 43.1 (#105)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1479 | 1413 |
Writing & Preference Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 70.2 (#22), Mistral Large 3: 60.0 (#101)
| Benchmark | Claude Sonnet 4.6 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1458 | 1428 |
| LMArena Creative Writing | 1435 | 1386 |
| EQ-Bench Creative Writing | 1810 | 1412 |
| LMArena Multi-Turn | 1464 | 1429 |
| EQ-Bench 4 | 1207 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than Mistral Large 3?
Claude Sonnet 4.6 is the stronger model overall, scoring 50.3 to 39.1 on the Noometry Index. Mistral Large 3 costs 16× less per token, which makes it the better buy when Claude Sonnet 4.6's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 4.6 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 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or Mistral Large 3 better for coding?
Claude Sonnet 4.6 scores higher on coding benchmarks: 46.3 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 4.6 does, with 1M tokens against 262K.
How many benchmarks do Claude Sonnet 4.6 and Mistral Large 3 share?
23 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and Mistral Large 3 has 24.