Model comparison
o3 vs Pixtral Large
o3 is the stronger model overall, scoring 47.5 to 32.2 on the Noometry Index.
Last verified . 3 shared benchmarks.
Mistral AISummary
- They share 3 benchmarks with published results for both. o3 scores higher in 3 categories and Pixtral Large in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3 leads 63.5 to 32.9.
- The biggest single-benchmark swing is EnigmaEval: 13.1% for o3 and 0.8% for Pixtral Large.
- Pixtral Large is cheaper at $2 / $6 per million input/output tokens, against $2 / $8 for o3.
- o3 accepts more context: 200K tokens versus 128K.
- Pixtral Large has downloadable open weights; the other is API-only.
Side by side
| o3 | Pixtral Large | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 47.5 | 32.2 |
| Released | 2025-04-16 | 2024-11-01 |
| Weights | Proprietary | Open |
| Context window | 200K | 128K |
| Max output | 100K | 128K |
| Input $ / M tokens | $2 | $2 |
| Output $ / M tokens | $8 | $6 |
| Results tracked | 63 | 3 |
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Category by category
Coding Not comparable
o3: 46.8 (#64), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| SWE-bench Verified | 62.3% | — |
| SWE-bench Verified (bash only) | 58.4% | — |
| Aider Polyglot | 81.3% | — |
| GSO | 8.8% | — |
| WeirdML | 52.4% | — |
| LMArena Coding | 1408 | — |
| CadEval | 74% | — |
| ALE-Bench | 933.55 | — |
Agentic & Tool Use Not comparable
o3: 34.5 (#44), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | 63% | — |
| GDPval | 30.8% | — |
| DeepResearch Bench | 45.2% | — |
| OSWorld | 23% | — |
| LMArena Search | 1144 | — |
| METR Time Horizons | 65.4% | — |
Reasoning o3 leads
o3: 32.0 (#78), Pixtral Large: 21.7 (#218)
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| EnigmaEval | 13.1% | 0.8% |
| ARC-AGI-2 | 6.5% | — |
| SimpleBench | 53.1% | — |
| Kagi LLM Benchmark | 67.6% | — |
| ARC-AGI-1 | 60.8% | — |
| CritPt | 1.4% | — |
| Chess Puzzles | 38% | — |
| LMArena Hard Prompts | 1402 | — |
| Mystery Game Puzzles | 29% | — |
| DTBench | 84.8% | — |
| LMCA | 39.7% | — |
| Epoch Capabilities Index | 146.86 | — |
| ForecastBench | 62.5 | — |
Math Not comparable
o3: 50.2 (#58), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| FrontierMath (Tiers 1-3) | 33.3% | — |
| OTIS Mock AIME 2024-2025 | 84.4% | — |
| Omni-MATH | 71.4% | — |
| LMArena Math | 1426 | — |
| MATH Level 5 | 97.8% | — |
| FrontierMath (Feb 2025 set) | 18.7% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Not comparable
o3: 54.6 (#52), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| GPQA Diamond | 81.8% | — |
| Humanity's Last Exam | 20.3% | — |
| SimpleQA Verified | 49.4% | — |
| MMLU-Pro | 85.9% | — |
| Confabulations | 14.4% | — |
| GPQA (HELM) | 75.3% | — |
| LMArena Expert | 1402 | — |
Multimodal o3 leads
o3: 41.4 (#36), Pixtral Large: 30.6 (#111)
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| LMArena Vision | 1214 | 1089 |
| GeoBench | 74% | — |
| VPCT | 52% | — |
Multilingual Not comparable
o3: 51.7 (#105), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1401 | — |
| LMArena Chinese | 1437 | — |
| LMArena French | 1430 | — |
| LMArena German | 1420 | — |
| LMArena Japanese | 1403 | — |
| LMArena Korean | 1370 | — |
| LMArena Russian | 1406 | — |
| LMArena Spanish | 1395 | — |
Instruction Following Not comparable
o3: 72.8 (#127), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| IFEval | 86.9% | — |
| LMArena Instruction Following | 1368 | — |
Long Context Not comparable
o3: 53.3 (#6), Pixtral Large: —
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| Fiction.LiveBench | 88.9% | — |
| CL-bench | 17.8% | — |
| LMArena Longer Query | 1372 | — |
Writing & Preference o3 leads
o3: 63.5 (#64), Pixtral Large: 32.9 (#278)
| Benchmark | o3 | Pixtral Large |
|---|---|---|
| EQ-Bench Creative Writing | 1676 | 988 |
| LMArena Text | 1410 | — |
| LMArena Creative Writing | 1359 | — |
| Short-Story Creative Writing | 83.9% | — |
| WildBench | 86.1% | — |
| LMArena Multi-Turn | 1405 | — |
Frequently asked questions
Is o3 better than Pixtral Large?
o3 is the stronger model overall, scoring 47.5 to 32.2 on the Noometry Index.
Which is cheaper, o3 or Pixtral Large?
Pixtral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o3 lists at $2 and $8.
Which has the bigger context window?
o3 does, with 200K tokens against 128K.
How many benchmarks do o3 and Pixtral Large share?
3 benchmarks have published results for both models. o3 has 63 scored results on Noometry and Pixtral Large has 3.