Model comparison
Mixtral 8x22B vs o1-pro
o1-pro is the stronger model overall, scoring 31.5 to 27.1 on the Noometry Index. Mixtral 8x22B costs 88× 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 29.7 to 15.1.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $150 / $600 for o1-pro.
- o1-pro accepts more context: 200K tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.
Side by side
| Mixtral 8x22B | o1-pro | |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 27.1 | 31.5 |
| Released | 2024-04-17 | 2025-03-19 |
| Weights | Open | Proprietary |
| Context window | 64K | 200K |
| Max output | 64K | 100K |
| Input $ / M tokens | $2 | $150 |
| Output $ / M tokens | $6 | $600 |
| Results tracked | 34 | 3 |
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Category by category
Coding Not comparable
Mixtral 8x22B: 24.2 (#329), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| WeirdML | 3.2% | — |
| BigCodeBench Instruct | 40.6% | — |
| LMArena Coding | 1166 | — |
| BigCodeBench Complete | 50.2% | — |
| HumanEval+ | 72% | — |
| MBPP+ | 64.3% | — |
Agentic & Tool Use Not comparable
Mixtral 8x22B: 23.1 (#127), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| Cybench | 7.5% | — |
Reasoning Too close to call
Mixtral 8x22B: 19.9 (#248), o1-pro: 20.4 (#239)
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| ARC-AGI-1 | — | 23.3% |
| EnigmaEval | — | 6.1% |
| LMArena Hard Prompts | 1150 | — |
| DTBench | 55.1% | — |
| Epoch Capabilities Index | 122.03 | — |
| ForecastBench | 56.3 | — |
Math Not comparable
Mixtral 8x22B: 22.9 (#275), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| Omni-MATH | 16.3% | — |
| LMArena Math | 1184 | — |
| MATH Level 5 | 24.2% | — |
Knowledge o1-pro leads
Mixtral 8x22B: 15.1 (#293), o1-pro: 29.7 (#234)
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| GPQA Diamond | 34.1% | — |
| Humanity's Last Exam | — | 8.1% |
| MMLU-Pro | 46% | — |
| GPQA (HELM) | 33.4% | — |
| LMArena Expert | 1113 | — |
| MMLU | 77.8% | — |
Multilingual Not comparable
Mixtral 8x22B: 32.8 (#255), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| LMArena Non-English | 1128 | — |
| LMArena Chinese | 1116 | — |
| LMArena French | 1166 | — |
| LMArena German | 1141 | — |
| LMArena Japanese | 1037 | — |
| LMArena Korean | 1057 | — |
| LMArena Russian | 1158 | — |
| LMArena Spanish | 1151 | — |
Instruction Following Not comparable
Mixtral 8x22B: 57.7 (#266), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| IFEval | 72.4% | — |
| LMArena Instruction Following | 1147 | — |
Long Context Not comparable
Mixtral 8x22B: 34.7 (#247), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| LMArena Longer Query | 1144 | — |
Writing & Preference Not comparable
Mixtral 8x22B: 36.9 (#262), o1-pro: —
| Benchmark | Mixtral 8x22B | o1-pro |
|---|---|---|
| LMArena Text | 1162 | — |
| LMArena Creative Writing | 1141 | — |
| WildBench | 71.1% | — |
| LMArena Multi-Turn | 1130 | — |
Frequently asked questions
Is Mixtral 8x22B better than o1-pro?
o1-pro is the stronger model overall, scoring 31.5 to 27.1 on the Noometry Index. Mixtral 8x22B costs 88× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Which is cheaper, Mixtral 8x22B or o1-pro?
Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
o1-pro does, with 200K tokens against 64K.
How many benchmarks do Mixtral 8x22B and o1-pro share?
0 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and o1-pro has 3.