Model comparison
Mistral 7B vs o3
o3 is the stronger model overall, scoring 47.5 to 23.0 on the Noometry Index. Mistral 7B costs 14× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
Mistral AISummary
- They share 22 benchmarks with published results for both. Mistral 7B scores higher in 0 categories and o3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o3 leads 54.6 to 7.4.
- The biggest single-benchmark swing is MATH Level 5: 3.7% for Mistral 7B and 97.8% for o3.
- Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $2 / $8 for o3.
- o3 accepts more context: 200K tokens versus 8K.
- Mistral 7B has downloadable open weights; the other is API-only.
Side by side
| Mistral 7B | o3 | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 23.0 | 47.5 |
| Released | 2023-09-27 | 2025-04-16 |
| Weights | Open | Proprietary |
| Context window | 8K | 200K |
| Max output | 8K | 100K |
| Input $ / M tokens | $0.25 | $2 |
| Output $ / M tokens | $0.25 | $8 |
| Results tracked | 37 | 63 |
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Category by category
Coding o3 leads
Mistral 7B: 26.4 (#326), o3: 46.8 (#64)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Coding | 1082 | 1408 |
| SWE-bench Verified | — | 62.3% |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| GSO | — | 8.8% |
| WeirdML | — | 52.4% |
| BigCodeBench Instruct | 19.5% | — |
| BigCodeBench Complete | 27.3% | — |
| CadEval | — | 74% |
| ALE-Bench | — | 933.55 |
| HumanEval+ | 36% | — |
| MBPP+ | 42.1% | — |
Agentic & Tool Use Not comparable
Mistral 7B: —, o3: 34.5 (#44)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| 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
Mistral 7B: 13.1 (#336), o3: 32.0 (#78)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| Chess Puzzles | 0% | 38% |
| LMArena Hard Prompts | 1067 | 1402 |
| DTBench | 42.5% | 84.8% |
| Epoch Capabilities Index | 112.21 | 146.86 |
| ARC-AGI-2 | — | 6.5% |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| ARC-AGI-1 | — | 60.8% |
| CritPt | — | 1.4% |
| EnigmaEval | — | 13.1% |
| Mystery Game Puzzles | — | 29% |
| LMCA | — | 39.7% |
| Adversarial NLI | 47.1% | — |
| BIG-Bench Hard | 56.1% | — |
| ForecastBench | — | 62.5 |
| HellaSwag | 81% | — |
| PIQA | 83% | — |
| WinoGrande | 75.3% | — |
Math o3 leads
Mistral 7B: 8.1 (#325), o3: 50.2 (#58)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.3% | 84.4% |
| LMArena Math | 1085 | 1426 |
| MATH Level 5 | 3.7% | 97.8% |
| FrontierMath (Tiers 1-3) | — | 33.3% |
| Omni-MATH | — | 71.4% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |
| GSM8K | 54.4% | — |
Knowledge o3 leads
Mistral 7B: 7.4 (#311), o3: 54.6 (#52)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| GPQA Diamond | 15.2% | 81.8% |
| LMArena Expert | 1036 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| SimpleQA Verified | — | 49.4% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| GPQA (HELM) | — | 75.3% |
| ARC (AI2) Challenge | 78.6% | — |
| BoolQ | 87.4% | — |
| MMLU | 62.5% | — |
| OpenBookQA | 79.8% | — |
| TriviaQA | 75.2% | — |
Multimodal Not comparable
Mistral 7B: —, o3: 41.4 (#36)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
Multilingual o3 leads
Mistral 7B: 25.8 (#283), o3: 51.7 (#105)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Non-English | 1012 | 1401 |
| LMArena Chinese | 1009 | 1437 |
| LMArena French | 1037 | 1430 |
| LMArena German | 987 | 1420 |
| LMArena Japanese | 878 | 1403 |
| LMArena Russian | 1018 | 1406 |
| LMArena Spanish | 1026 | 1395 |
| LMArena Korean | — | 1370 |
Instruction Following o3 leads
Mistral 7B: 54.2 (#280), o3: 72.8 (#127)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Instruction Following | 1060 | 1368 |
| IFEval | — | 86.9% |
Long Context o3 leads
Mistral 7B: 32.2 (#271), o3: 53.3 (#6)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Longer Query | 1060 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
Writing & Preference o3 leads
Mistral 7B: 30.7 (#286), o3: 63.5 (#64)
| Benchmark | Mistral 7B | o3 |
|---|---|---|
| LMArena Text | 1090 | 1410 |
| LMArena Creative Writing | 1068 | 1359 |
| LMArena Multi-Turn | 1062 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| EQ-Bench Creative Writing | — | 1676 |
| WildBench | — | 86.1% |
Frequently asked questions
Is Mistral 7B better than o3?
o3 is the stronger model overall, scoring 47.5 to 23.0 on the Noometry Index. Mistral 7B costs 14× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.
Which is cheaper, Mistral 7B or o3?
Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; o3 lists at $2 and $8.
Is Mistral 7B or o3 better for coding?
o3 scores higher on coding benchmarks: 46.8 versus 26.4 in the Noometry coding category.
Which has the bigger context window?
o3 does, with 200K tokens against 8K.
How many benchmarks do Mistral 7B and o3 share?
22 benchmarks have published results for both models. Mistral 7B has 37 scored results on Noometry and o3 has 63.