# Mixtral 8x22B vs o1

> o1 is the stronger model overall, scoring 40.6 to 26.7 on the Noometry Index. Mixtral 8x22B costs 8.8× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/mixtral-8x22b-vs-o1
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. Mixtral 8x22B scores higher in 0 categories and o1 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o1 leads 41.5 to 15.1.
- The biggest single-benchmark swing is MATH Level 5: 24.2% for Mixtral 8x22B and 94.7% for o1.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $15 / $60 for o1.
- o1 accepts more context: 200K tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.

## Snapshot

| | Mixtral 8x22B | o1 |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 26.7 | 40.6 |
| Rank | 330 | 140 |
| Context | 64K | 200K |
| Input $/M | $2 | $15 |
| Output $/M | $6 | $60 |
| Weights | Open | Proprietary |

## Coding

- Mixtral 8x22B: 23.8 (#324)
- o1: 45.7 (#64)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| WeirdML | 3.2% | 47.6% |
| LMArena Coding | 1166 | 1367 |
| HumanEval+ | 72% | 89% |
| MBPP+ | 64.3% | 80.2% |
| Aider Polyglot | — | 61.7% |
| BigCodeBench Instruct | 40.6% | — |
| LiveBench Coding | — | 69.7% |
| BigCodeBench Complete | 50.2% | — |
| CadEval | — | 56% |

## Agentic & Tool Use

- Mixtral 8x22B: 22.8 (#119)
- o1: 24.3 (#111)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| Cybench | 7.5% | 10% |
| METR Time Horizons | — | 51.1% |

## Reasoning

- Mixtral 8x22B: 19.1 (#246)
- o1: 27.5 (#103)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Hard Prompts | 1150 | 1372 |
| DTBench | 55.1% | 74.7% |
| Epoch Capabilities Index | 122 | 141.92 |
| SimpleBench | — | 41.7% |
| ARC-AGI-1 | — | 30.7% |
| Chess Puzzles | — | 15% |
| EnigmaEval | — | 5.7% |
| LiveBench Reasoning | — | 91.6% |
| LiveBench Data Analysis | — | 65.5% |
| LMCA | — | 22.3% |
| ForecastBench | 56.3 | — |
| LiveBench | — | 75.7% |

## Math

- Mixtral 8x22B: 21.2 (#271)
- o1: 34.9 (#150)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Math | 1184 | 1388 |
| MATH Level 5 | 24.2% | 94.7% |
| FrontierMath (Tiers 1-3) | — | 14.7% |
| OTIS Mock AIME 2024-2025 | — | 73.3% |
| Omni-MATH | 16.3% | — |
| LiveBench Math | — | 80.3% |
| FrontierMath (Feb 2025 set) | — | 9.3% |

## Knowledge

- Mixtral 8x22B: 15.1 (#288)
- o1: 41.5 (#101)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| GPQA Diamond | 34.1% | 76.8% |
| LMArena Expert | 1113 | 1362 |
| Humanity's Last Exam | — | 8% |
| SimpleQA Verified | — | 41.1% |
| MMLU-Pro | 46% | — |
| Confabulations | — | 11.7% |
| GPQA (HELM) | 33.4% | — |
| MMLU | 77.8% | — |

## Multimodal

- Mixtral 8x22B: —
- o1: 33.6 (#87)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Vision | — | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| SpatialViz-Bench | — | 41.4% |

## Multilingual

- Mixtral 8x22B: 32.9 (#250)
- o1: 48.8 (#137)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Non-English | 1128 | 1359 |
| LMArena Chinese | 1116 | 1394 |
| LMArena French | 1165 | 1343 |
| LMArena German | 1141 | 1337 |
| LMArena Japanese | 1037 | 1346 |
| LMArena Korean | 1056 | 1396 |
| LMArena Russian | 1158 | 1356 |
| LMArena Spanish | 1150 | 1345 |

## Instruction Following

- Mixtral 8x22B: 57.9 (#261)
- o1: 75.0 (#82)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Instruction Following | 1147 | 1368 |
| LiveBench Instruction Following | — | 81.5% |
| IFEval | 72.4% | — |

## Long Context

- Mixtral 8x22B: 34.6 (#242)
- o1: 50.3 (#9)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Longer Query | 1144 | 1378 |
| Fiction.LiveBench | — | 83.3% |

## Writing & Preference

- Mixtral 8x22B: 37.1 (#257)
- o1: 55.8 (#139)

| Benchmark | Mixtral 8x22B | o1 |
|---|---|---|
| LMArena Text | 1162 | 1366 |
| LMArena Creative Writing | 1141 | 1347 |
| LMArena Multi-Turn | 1130 | 1368 |
| Short-Story Creative Writing | — | 70.2% |
| WildBench | 71.1% | — |
| LiveBench Language | — | 65.4% |

## FAQ

### Is Mixtral 8x22B better than o1?

o1 is the stronger model overall, scoring 40.6 to 26.7 on the Noometry Index. Mixtral 8x22B 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, Mixtral 8x22B or o1?

Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; o1 lists at $15 and $60.

### Is Mixtral 8x22B or o1 better for coding?

o1 scores higher on coding benchmarks: 45.7 versus 23.8 in the Noometry coding category.

### Which has the bigger context window?

o1 does, with 200K tokens against 64K.

### How many benchmarks do Mixtral 8x22B and o1 share?

25 benchmarks have published results for both models. Mixtral 8x22B has 34 scored results on Noometry and o1 has 52.