Model comparison
Mixtral 8x7B vs o1-pro
o1-pro is the stronger model overall, scoring 31.2 to 26.8 on the Noometry Index. Mixtral 8x7B costs 375× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
Mistral AISummary
- The widest gap is in knowledge, where o1-pro leads 29.3 to 11.0.
- Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $150 / $600 for o1-pro.
- o1-pro accepts more context: 200K tokens versus 32K.
- Mixtral 8x7B has downloadable open weights; the other is API-only.
Side by side
| Mixtral 8x7B | o1-pro | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 26.8 | 31.2 |
| Released | 2023-12-11 | 2025-03-19 |
| Weights | Open | Proprietary |
| Context window | 32K | 200K |
| Max output | 32K | 100K |
| Input $ / M tokens | $0.70 | $150 |
| Output $ / M tokens | $0.70 | $600 |
| Results tracked | 38 | 3 |
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Category by category
Coding Not comparable
Mixtral 8x7B: 32.2 (#265), o1-pro: —
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| LMArena Coding | 1127 | — |
| HumanEval+ | 39.6% | — |
| MBPP+ | 49.7% | — |
Reasoning o1-pro leads
Mixtral 8x7B: 17.4 (#283), o1-pro: 20.2 (#223)
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| ARC-AGI-1 | — | 23.3% |
| EnigmaEval | — | 6.1% |
| LMArena Hard Prompts | 1115 | — |
| DTBench | 49.6% | — |
| Adversarial NLI | 55.2% | — |
| Epoch Capabilities Index | 118.38 | — |
| ForecastBench | 56.3 | — |
| HellaSwag | 86.7% | — |
| PIQA | 83.6% | — |
| WinoGrande | 77.2% | — |
Math Not comparable
Mixtral 8x7B: 17.2 (#284), o1-pro: —
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| Omni-MATH | 10.5% | — |
| LMArena Math | 1147 | — |
| MATH Level 5 | 10% | — |
| GSM8K | 74.4% | — |
Knowledge o1-pro leads
Mixtral 8x7B: 11.0 (#296), o1-pro: 29.3 (#227)
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| GPQA Diamond | 30.6% | — |
| Humanity's Last Exam | — | 8.1% |
| MMLU-Pro | 33.5% | — |
| GPQA (HELM) | 29.6% | — |
| LMArena Expert | 1088 | — |
| ARC (AI2) Challenge | 87.3% | — |
| MMLU | 70.6% | — |
| OpenBookQA | 85.8% | — |
| TriviaQA | 82.2% | — |
Multilingual Not comparable
Mixtral 8x7B: 29.8 (#261), o1-pro: —
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| LMArena Non-English | 1077 | — |
| LMArena Chinese | 1055 | — |
| LMArena French | 1165 | — |
| LMArena German | 1114 | — |
| LMArena Japanese | 931 | — |
| LMArena Korean | 968 | — |
| LMArena Russian | 1090 | — |
| LMArena Spanish | 1110 | — |
Instruction Following Not comparable
Mixtral 8x7B: 51.2 (#292), o1-pro: —
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| IFEval | 57.5% | — |
| LMArena Instruction Following | 1110 | — |
Long Context Not comparable
Mixtral 8x7B: 33.4 (#255), o1-pro: —
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| LMArena Longer Query | 1103 | — |
Writing & Preference Not comparable
Mixtral 8x7B: 34.4 (#265), o1-pro: —
| Benchmark | Mixtral 8x7B | o1-pro |
|---|---|---|
| LMArena Text | 1132 | — |
| LMArena Creative Writing | 1109 | — |
| WildBench | 67.3% | — |
| LMArena Multi-Turn | 1115 | — |
Frequently asked questions
Is Mixtral 8x7B better than o1-pro?
o1-pro is the stronger model overall, scoring 31.2 to 26.8 on the Noometry Index. Mixtral 8x7B costs 375× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Which is cheaper, Mixtral 8x7B or o1-pro?
Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
o1-pro does, with 200K tokens against 32K.
How many benchmarks do Mixtral 8x7B and o1-pro share?
0 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and o1-pro has 3.