Model comparison
Claude Opus 4.7 vs Mistral Large 3
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 39.1 on the Noometry Index. Mistral Large 3 costs 27× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.
Last verified . 24 shared benchmarks.
Mistral AISummary
- They share 24 benchmarks with published results for both. Claude Opus 4.7 scores higher in 9 categories and Mistral Large 3 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Opus 4.7 leads 53.8 to 15.2.
- The biggest single-benchmark swing is Thematic Generalization: 72.8% for Claude Opus 4.7 and 23% for Mistral Large 3.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- Claude Opus 4.7 accepts more context: 1M tokens versus 262K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4.7 | Mistral Large 3 | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 58.3 | 39.1 |
| Released | 2026-04-14 | 2025-12-02 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 128K | 8K |
| Input $ / M tokens | $5 | $0.25 |
| Output $ / M tokens | $25 | $0.75 |
| Results tracked | 66 | 24 |
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Category by category
Coding Claude Opus 4.7 leads
Claude Opus 4.7: 59.6 (#13), Mistral Large 3: 34.4 (#237)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena WebDev | 1558 | 1230 |
| LMArena Coding | 1518 | 1448 |
| SWE-bench Verified | 83.5% | — |
| FrontierCode | 38.5% | — |
| SciCode | 54.5% | — |
| GSO | 44.1% | — |
| WeirdML | 76.4% | — |
| MirrorCode | 31.1% | — |
| ALE-Bench | 1,323 | — |
Agentic & Tool Use Not comparable
Claude Opus 4.7: 47.9 (#10), Mistral Large 3: —
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Terminal-Bench | 80.2% | — |
| APEX-Agents | 49.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |
| Vending-Bench 2 | 10,937 | — |
Reasoning Claude Opus 4.7 leads
Claude Opus 4.7: 53.8 (#29), Mistral Large 3: 15.2 (#319)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Kagi LLM Benchmark | 80.7% | 50.9% |
| NYT Connections (extended) | 39% | 7.5% |
| Thematic Generalization | 72.8% | 23% |
| LMArena Hard Prompts | 1506 | 1429 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| ARC-AGI-1 | 93.5% | — |
| CritPt | 12% | — |
| Chess Puzzles | 30% | — |
| EBR-Bench | 19% | — |
| Mystery Game Puzzles | 28% | — |
| DTBench | 94.7% | — |
| LMCA | 52.2% | — |
| Epoch Capabilities Index | 156.25 | — |
| ForecastBench | 60.3 | — |
Math Claude Opus 4.7 leads
Claude Opus 4.7: 66.7 (#26), Mistral Large 3: 38.7 (#129)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Math | 1499 | 1414 |
| FrontierMath (Tiers 1-3) | 70.2% | — |
| FrontierMath Tier 4 | 31.7% | — |
| MathArena Final-Answer Competitions | 73.6% | — |
| OTIS Mock AIME 2024-2025 | 97.8% | — |
| ProofBench | 54% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |
Knowledge Claude Opus 4.7 leads
Claude Opus 4.7: 62.6 (#23), Mistral Large 3: 36.0 (#177)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| Vectara Hallucination Rate | 12% | 14.5% |
| LMArena Expert | 1521 | 1421 |
| GPQA Diamond | 90.2% | — |
| Humanity's Last Exam | 36.2% | — |
| SimpleQA Verified | 51.7% | — |
Multimodal Claude Opus 4.7 leads
Claude Opus 4.7: 41.2 (#38), Mistral Large 3: 38.2 (#66)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Vision | 1316 | 1221 |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |
Multilingual Claude Opus 4.7 leads
Claude Opus 4.7: 57.3 (#10), Mistral Large 3: 52.5 (#84)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Non-English | 1480 | 1413 |
| LMArena Chinese | 1531 | 1447 |
| LMArena French | 1503 | 1455 |
| LMArena German | 1495 | 1437 |
| LMArena Japanese | 1472 | 1394 |
| LMArena Korean | 1464 | 1384 |
| LMArena Russian | 1494 | 1411 |
| LMArena Spanish | 1495 | 1440 |
Instruction Following Claude Opus 4.7 leads
Claude Opus 4.7: 78.4 (#10), Mistral Large 3: 74.0 (#108)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Instruction Following | 1498 | 1403 |
Long Context Claude Opus 4.7 leads
Claude Opus 4.7: 46.2 (#25), Mistral Large 3: 43.1 (#105)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Longer Query | 1505 | 1413 |
Writing & Preference Claude Opus 4.7 leads
Claude Opus 4.7: 75.1 (#8), Mistral Large 3: 60.0 (#101)
| Benchmark | Claude Opus 4.7 | Mistral Large 3 |
|---|---|---|
| LMArena Text | 1490 | 1428 |
| LMArena Creative Writing | 1486 | 1386 |
| EQ-Bench Creative Writing | 1914 | 1412 |
| LMArena Multi-Turn | 1505 | 1429 |
| EQ-Bench 4 | 1311 | — |
Frequently asked questions
Is Claude Opus 4.7 better than Mistral Large 3?
Claude Opus 4.7 is the stronger model overall, scoring 58.3 to 39.1 on the Noometry Index. Mistral Large 3 costs 27× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4.7 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 Opus 4.7 lists at $5 and $25.
Is Claude Opus 4.7 or Mistral Large 3 better for coding?
Claude Opus 4.7 scores higher on coding benchmarks: 59.6 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Claude Opus 4.7 does, with 1M tokens against 262K.
How many benchmarks do Claude Opus 4.7 and Mistral Large 3 share?
24 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and Mistral Large 3 has 24.