Model comparison
o1 vs Pixtral Large
o1 is the stronger model overall, scoring 40.9 to 32.2 on the Noometry Index. Pixtral Large costs 8.8× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Mistral AISummary
- They share 2 benchmarks with published results for both. o1 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 o1 leads 55.6 to 32.9.
- Pixtral Large is cheaper at $2 / $6 per million input/output tokens, against $15 / $60 for o1.
- o1 accepts more context: 200K tokens versus 128K.
- Pixtral Large has downloadable open weights; the other is API-only.
Side by side
| o1 | Pixtral Large | |
|---|---|---|
| Provider | OpenAI | Mistral AI |
| Noometry Index | 40.9 | 32.2 |
| Released | 2024-09-12 | 2024-11-01 |
| Weights | Proprietary | Open |
| Context window | 200K | 128K |
| Max output | 100K | 128K |
| Input $ / M tokens | $15 | $2 |
| Output $ / M tokens | $60 | $6 |
| Results tracked | 52 | 3 |
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Category by category
Coding Not comparable
o1: 46.1 (#70), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| Aider Polyglot | 61.7% | — |
| WeirdML | 47.6% | — |
| LiveBench Coding | 69.7% | — |
| LMArena Coding | 1367 | — |
| CadEval | 56% | — |
| HumanEval+ | 89% | — |
| MBPP+ | 80.2% | — |
Agentic & Tool Use Not comparable
o1: 24.6 (#117), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| Cybench | 10% | — |
| METR Time Horizons | 51.1% | — |
Reasoning o1 leads
o1: 27.9 (#111), Pixtral Large: 21.7 (#218)
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| EnigmaEval | 5.7% | 0.8% |
| SimpleBench | 41.7% | — |
| ARC-AGI-1 | 30.7% | — |
| Chess Puzzles | 15% | — |
| LiveBench Reasoning | 91.6% | — |
| LMArena Hard Prompts | 1371 | — |
| DTBench | 74.7% | — |
| LiveBench Data Analysis | 65.5% | — |
| LMCA | 22.3% | — |
| Epoch Capabilities Index | 141.91 | — |
| LiveBench | 75.7% | — |
Math Not comparable
o1: 36.1 (#175), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| FrontierMath (Tiers 1-3) | 14.7% | — |
| OTIS Mock AIME 2024-2025 | 73.3% | — |
| LiveBench Math | 80.3% | — |
| LMArena Math | 1388 | — |
| MATH Level 5 | 94.7% | — |
| FrontierMath (Feb 2025 set) | 9.3% | — |
Knowledge Not comparable
o1: 41.5 (#110), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| GPQA Diamond | 76.8% | — |
| Humanity's Last Exam | 8% | — |
| SimpleQA Verified | 41.1% | — |
| Confabulations | 11.7% | — |
| LMArena Expert | 1361 | — |
Multimodal o1 leads
o1: 34.2 (#93), Pixtral Large: 30.6 (#111)
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| LMArena Vision | 1168 | 1089 |
| GeoBench | 80% | — |
| VPCT | 37% | — |
| SpatialViz-Bench | 41.4% | — |
Multilingual Not comparable
o1: 48.6 (#142), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| LMArena Non-English | 1358 | — |
| LMArena Chinese | 1394 | — |
| LMArena French | 1344 | — |
| LMArena German | 1337 | — |
| LMArena Japanese | 1346 | — |
| LMArena Korean | 1396 | — |
| LMArena Russian | 1356 | — |
| LMArena Spanish | 1345 | — |
Instruction Following Not comparable
o1: 74.8 (#86), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| LiveBench Instruction Following | 81.5% | — |
| LMArena Instruction Following | 1367 | — |
Long Context Not comparable
o1: 50.3 (#9), Pixtral Large: —
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| Fiction.LiveBench | 83.3% | — |
| LMArena Longer Query | 1378 | — |
Writing & Preference o1 leads
o1: 55.6 (#144), Pixtral Large: 32.9 (#278)
| Benchmark | o1 | Pixtral Large |
|---|---|---|
| LMArena Text | 1366 | — |
| LMArena Creative Writing | 1348 | — |
| Short-Story Creative Writing | 70.2% | — |
| EQ-Bench Creative Writing | — | 988 |
| LMArena Multi-Turn | 1369 | — |
| LiveBench Language | 65.4% | — |
Frequently asked questions
Is o1 better than Pixtral Large?
o1 is the stronger model overall, scoring 40.9 to 32.2 on the Noometry Index. Pixtral Large costs 8.8× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Which is cheaper, o1 or Pixtral Large?
Pixtral Large is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o1 lists at $15 and $60.
Which has the bigger context window?
o1 does, with 200K tokens against 128K.
How many benchmarks do o1 and Pixtral Large share?
2 benchmarks have published results for both models. o1 has 52 scored results on Noometry and Pixtral Large has 3.