Model comparison
Mistral Large 3 vs o1
o1 is the stronger model overall, scoring 40.9 to 39.1 on the Noometry Index. Mistral Large 3 costs 70× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Mistral AISummary
- They share 18 benchmarks with published results for both. Mistral Large 3 scores higher in 4 categories and o1 in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where o1 leads 27.9 to 15.2.
- Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $15 / $60 for o1.
- Mistral Large 3 accepts more context: 262K tokens versus 200K.
- Mistral Large 3 has downloadable open weights; the other is API-only.
Side by side
| Mistral Large 3 | o1 | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 39.1 | 40.9 |
| Released | 2025-12-02 | 2024-09-12 |
| Weights | Open | Proprietary |
| Context window | 262K | 200K |
| Max output | 8K | 100K |
| Input $ / M tokens | $0.25 | $15 |
| Output $ / M tokens | $0.75 | $60 |
| Results tracked | 24 | 52 |
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Category by category
Coding o1 leads
Mistral Large 3: 34.4 (#237), o1: 46.1 (#70)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Coding | 1448 | 1367 |
| Aider Polyglot | — | 61.7% |
| LMArena WebDev | 1230 | — |
| WeirdML | — | 47.6% |
| LiveBench Coding | — | 69.7% |
| CadEval | — | 56% |
| HumanEval+ | — | 89% |
| MBPP+ | — | 80.2% |
Agentic & Tool Use Not comparable
Mistral Large 3: —, o1: 24.6 (#117)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |
Reasoning o1 leads
Mistral Large 3: 15.2 (#319), o1: 27.9 (#111)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1371 |
| SimpleBench | — | 41.7% |
| Kagi LLM Benchmark | 50.9% | — |
| NYT Connections (extended) | 7.5% | — |
| ARC-AGI-1 | — | 30.7% |
| Chess Puzzles | — | 15% |
| EnigmaEval | — | 5.7% |
| Thematic Generalization | 23% | — |
| LiveBench Reasoning | — | 91.6% |
| DTBench | — | 74.7% |
| LiveBench Data Analysis | — | 65.5% |
| LMCA | — | 22.3% |
| Epoch Capabilities Index | — | 141.91 |
| LiveBench | — | 75.7% |
Math Mistral Large 3 leads
Mistral Large 3: 38.7 (#129), o1: 36.1 (#175)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Math | 1414 | 1388 |
| FrontierMath (Tiers 1-3) | — | 14.7% |
| OTIS Mock AIME 2024-2025 | — | 73.3% |
| LiveBench Math | — | 80.3% |
| MATH Level 5 | — | 94.7% |
| FrontierMath (Feb 2025 set) | — | 9.3% |
Knowledge o1 leads
Mistral Large 3: 36.0 (#177), o1: 41.5 (#110)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Expert | 1421 | 1361 |
| GPQA Diamond | — | 76.8% |
| Humanity's Last Exam | — | 8% |
| SimpleQA Verified | — | 41.1% |
| Confabulations | — | 11.7% |
| Vectara Hallucination Rate | 14.5% | — |
Multimodal Mistral Large 3 leads
Mistral Large 3: 38.2 (#66), o1: 34.2 (#93)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Vision | 1221 | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| SpatialViz-Bench | — | 41.4% |
Multilingual Mistral Large 3 leads
Mistral Large 3: 52.5 (#84), o1: 48.6 (#142)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Non-English | 1413 | 1358 |
| LMArena Chinese | 1447 | 1394 |
| LMArena French | 1455 | 1344 |
| LMArena German | 1437 | 1337 |
| LMArena Japanese | 1394 | 1346 |
| LMArena Korean | 1384 | 1396 |
| LMArena Russian | 1411 | 1356 |
| LMArena Spanish | 1440 | 1345 |
Instruction Following Too close to call
Mistral Large 3: 74.0 (#108), o1: 74.8 (#86)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Instruction Following | 1403 | 1367 |
| LiveBench Instruction Following | — | 81.5% |
Long Context o1 leads
Mistral Large 3: 43.1 (#105), o1: 50.3 (#9)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Longer Query | 1413 | 1378 |
| Fiction.LiveBench | — | 83.3% |
Writing & Preference Mistral Large 3 leads
Mistral Large 3: 60.0 (#101), o1: 55.6 (#144)
| Benchmark | Mistral Large 3 | o1 |
|---|---|---|
| LMArena Text | 1428 | 1366 |
| LMArena Creative Writing | 1386 | 1348 |
| LMArena Multi-Turn | 1429 | 1369 |
| Short-Story Creative Writing | — | 70.2% |
| EQ-Bench Creative Writing | 1412 | — |
| LiveBench Language | — | 65.4% |
Frequently asked questions
Is Mistral Large 3 better than o1?
o1 is the stronger model overall, scoring 40.9 to 39.1 on the Noometry Index. Mistral Large 3 costs 70× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.
Which is cheaper, Mistral Large 3 or o1?
Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; o1 lists at $15 and $60.
Is Mistral Large 3 or o1 better for coding?
o1 scores higher on coding benchmarks: 46.1 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
Mistral Large 3 does, with 262K tokens against 200K.
How many benchmarks do Mistral Large 3 and o1 share?
18 benchmarks have published results for both models. Mistral Large 3 has 24 scored results on Noometry and o1 has 52.