Model comparison
Claude Opus 4 vs Pixtral Large
Claude Opus 4 is the stronger model overall, scoring 43.1 to 32.2 on the Noometry Index. Pixtral Large costs 10× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Last verified . 3 shared benchmarks.
Mistral AISummary
- They share 3 benchmarks with published results for both. Claude Opus 4 scores higher in 3 categories and Pixtral Large in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude Opus 4 leads 61.2 to 32.9.
- Pixtral Large is cheaper at $2 / $6 per million input/output tokens, against $15 / $75 for Claude Opus 4.
- Claude Opus 4 accepts more context: 200K tokens versus 128K.
- Pixtral Large has downloadable open weights; the other is API-only.
Side by side
| Claude Opus 4 | Pixtral Large | |
|---|---|---|
| Provider | Anthropic | Mistral AI |
| Noometry Index | 43.1 | 32.2 |
| Released | 2025-05-22 | 2024-11-01 |
| Weights | Proprietary | Open |
| Context window | 200K | 128K |
| Max output | 32K | 128K |
| Input $ / M tokens | $15 | $2 |
| Output $ / M tokens | $75 | $6 |
| Results tracked | 56 | 3 |
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Category by category
Coding Not comparable
Claude Opus 4: 47.2 (#62), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| SWE-bench Verified | 70.7% | — |
| SWE-bench Verified (bash only) | 67.6% | — |
| Aider Polyglot | 72% | — |
| GSO | 6.9% | — |
| WeirdML | 43.7% | — |
| LMArena Coding | 1442 | — |
| AlgoTune | 1.33 | — |
Agentic & Tool Use Not comparable
Claude Opus 4: 34.8 (#42), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| Cybench | 38% | — |
| DeepResearch Bench | 46.8% | — |
| LMArena Search | 1127 | — |
| METR Time Horizons | 63.9% | — |
Reasoning Claude Opus 4 leads
Claude Opus 4: 27.3 (#121), Pixtral Large: 21.7 (#218)
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| EnigmaEval | 5.6% | 0.8% |
| ARC-AGI-2 | 8.6% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 74.3% | — |
| ARC-AGI-1 | 35.7% | — |
| CritPt | 0.3% | — |
| LMArena Hard Prompts | 1399 | — |
| DTBench | 81.6% | — |
| LMCA | 37.4% | — |
| Epoch Capabilities Index | 142.67 | — |
| ForecastBench | 61.1 | — |
Math Not comparable
Claude Opus 4: 42.0 (#86), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 64.4% | — |
| Omni-MATH | 61.6% | — |
| LMArena Math | 1390 | — |
| MATH Level 5 | 85% | — |
| FrontierMath (Feb 2025 set) | 4.5% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Not comparable
Claude Opus 4: 44.0 (#88), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| GPQA Diamond | 76.3% | — |
| Humanity's Last Exam | 10.7% | — |
| MMLU-Pro | 87.5% | — |
| Confabulations | 15.9% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 70.8% | — |
| LMArena Expert | 1386 | — |
Multimodal Too close to call
Claude Opus 4: 31.5 (#106), Pixtral Large: 30.6 (#111)
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| LMArena Vision | 1192 | 1089 |
| GeoBench | 49% | — |
| VPCT | 38% | — |
Multilingual Not comparable
Claude Opus 4: 48.8 (#138), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1362 | — |
| LMArena Chinese | 1386 | — |
| LMArena French | 1372 | — |
| LMArena German | 1391 | — |
| LMArena Japanese | 1331 | — |
| LMArena Korean | 1321 | — |
| LMArena Russian | 1392 | — |
| LMArena Spanish | 1389 | — |
Instruction Following Not comparable
Claude Opus 4: 77.1 (#28), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| IFEval | 91.8% | — |
| LMArena Instruction Following | 1406 | — |
Long Context Not comparable
Claude Opus 4: 39.6 (#172), Pixtral Large: —
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| Fiction.LiveBench | 61.1% | — |
| LMArena Longer Query | 1422 | — |
Writing & Preference Claude Opus 4 leads
Claude Opus 4: 61.2 (#89), Pixtral Large: 32.9 (#278)
| Benchmark | Claude Opus 4 | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 1580 | 988 |
| LMArena Text | 1377 | — |
| LMArena Creative Writing | 1387 | — |
| Short-Story Creative Writing | 83.6% | — |
| WildBench | 85.2% | — |
| LMArena Multi-Turn | 1396 | — |
Frequently asked questions
Is Claude Opus 4 better than Pixtral Large?
Claude Opus 4 is the stronger model overall, scoring 43.1 to 32.2 on the Noometry Index. Pixtral Large costs 10× less per token, which makes it the better buy when Claude Opus 4's lead doesn't matter for your workload.
Which is cheaper, Claude Opus 4 or Pixtral Large?
Pixtral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Claude Opus 4 lists at $15 and $75.
Which has the bigger context window?
Claude Opus 4 does, with 200K tokens against 128K.
How many benchmarks do Claude Opus 4 and Pixtral Large share?
3 benchmarks have published results for both models. Claude Opus 4 has 56 scored results on Noometry and Pixtral Large has 3.