# Mixtral 8x7B vs o1

> o1 is the stronger model overall, scoring 40.9 to 27.1 on the Noometry Index. Mixtral 8x7B costs 38× 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-8x7b-vs-o1
- Last updated: 2026-10-10
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. Mixtral 8x7B scores higher in 0 categories and o1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where o1 leads 41.5 to 11.0.
- The biggest single-benchmark swing is MATH Level 5: 10% for Mixtral 8x7B and 94.7% for o1.
- Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $15 / $60 for o1.
- o1 accepts more context: 200K tokens versus 32K.
- Mixtral 8x7B has downloadable open weights; the other is API-only.

## Snapshot

| | Mixtral 8x7B | o1 |
|---|---|---|
| Provider | Mistral AI | OpenAI |
| Noometry Index | 27.1 | 40.9 |
| Rank | 334 | 143 |
| Context | 32K | 200K |
| Input $/M | $0.70 | $15 |
| Output $/M | $0.70 | $60 |
| Weights | Open | Proprietary |

## Coding

- Mixtral 8x7B: 32.8 (#269)
- o1: 46.1 (#70)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Coding | 1126 | 1367 |
| HumanEval+ | 39.6% | 89% |
| MBPP+ | 49.7% | 80.2% |
| Aider Polyglot | — | 61.7% |
| WeirdML | — | 47.6% |
| LiveBench Coding | — | 69.7% |
| CadEval | — | 56% |

## Agentic & Tool Use

- Mixtral 8x7B: —
- o1: 24.6 (#117)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| Cybench | — | 10% |
| METR Time Horizons | — | 51.1% |

## Reasoning

- Mixtral 8x7B: 18.2 (#285)
- o1: 27.9 (#111)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Hard Prompts | 1115 | 1371 |
| DTBench | 49.6% | 74.7% |
| Epoch Capabilities Index | 118.47 | 141.91 |
| 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% |
| Adversarial NLI | 55.2% | — |
| ForecastBench | 56.3 | — |
| HellaSwag | 86.7% | — |
| LiveBench | — | 75.7% |
| PIQA | 83.6% | — |
| WinoGrande | 77.2% | — |

## Math

- Mixtral 8x7B: 18.8 (#289)
- o1: 36.1 (#175)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Math | 1147 | 1388 |
| MATH Level 5 | 10% | 94.7% |
| FrontierMath (Tiers 1-3) | — | 14.7% |
| OTIS Mock AIME 2024-2025 | — | 73.3% |
| Omni-MATH | 10.5% | — |
| LiveBench Math | — | 80.3% |
| FrontierMath (Feb 2025 set) | — | 9.3% |
| GSM8K | 74.4% | — |

## Knowledge

- Mixtral 8x7B: 11.0 (#301)
- o1: 41.5 (#110)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| GPQA Diamond | 30.6% | 76.8% |
| LMArena Expert | 1088 | 1361 |
| Humanity's Last Exam | — | 8% |
| SimpleQA Verified | — | 41.1% |
| MMLU-Pro | 33.5% | — |
| Confabulations | — | 11.7% |
| GPQA (HELM) | 29.6% | — |
| ARC (AI2) Challenge | 87.3% | — |
| MMLU | 70.6% | — |
| OpenBookQA | 85.8% | — |
| TriviaQA | 82.2% | — |

## Multimodal

- Mixtral 8x7B: —
- o1: 34.2 (#93)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Vision | — | 1168 |
| GeoBench | — | 80% |
| VPCT | — | 37% |
| SpatialViz-Bench | — | 41.4% |

## Multilingual

- Mixtral 8x7B: 29.6 (#266)
- o1: 48.6 (#142)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Non-English | 1077 | 1358 |
| LMArena Chinese | 1055 | 1394 |
| LMArena French | 1166 | 1344 |
| LMArena German | 1114 | 1337 |
| LMArena Japanese | 931 | 1346 |
| LMArena Korean | 968 | 1396 |
| LMArena Russian | 1090 | 1356 |
| LMArena Spanish | 1111 | 1345 |

## Instruction Following

- Mixtral 8x7B: 51.0 (#297)
- o1: 74.8 (#86)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Instruction Following | 1109 | 1367 |
| LiveBench Instruction Following | — | 81.5% |
| IFEval | 57.5% | — |

## Long Context

- Mixtral 8x7B: 33.4 (#260)
- o1: 50.3 (#9)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Longer Query | 1103 | 1378 |
| Fiction.LiveBench | — | 83.3% |

## Writing & Preference

- Mixtral 8x7B: 34.2 (#270)
- o1: 55.6 (#144)

| Benchmark | Mixtral 8x7B | o1 |
|---|---|---|
| LMArena Text | 1132 | 1366 |
| LMArena Creative Writing | 1109 | 1348 |
| LMArena Multi-Turn | 1115 | 1369 |
| Short-Story Creative Writing | — | 70.2% |
| WildBench | 67.3% | — |
| LiveBench Language | — | 65.4% |

## FAQ

### Is Mixtral 8x7B better than o1?

o1 is the stronger model overall, scoring 40.9 to 27.1 on the Noometry Index. Mixtral 8x7B costs 38× less per token, which makes it the better buy when o1's lead doesn't matter for your workload.

### Which is cheaper, Mixtral 8x7B or o1?

Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; o1 lists at $15 and $60.

### Is Mixtral 8x7B or o1 better for coding?

o1 scores higher on coding benchmarks: 46.1 versus 32.8 in the Noometry coding category.

### Which has the bigger context window?

o1 does, with 200K tokens against 32K.

### How many benchmarks do Mixtral 8x7B and o1 share?

23 benchmarks have published results for both models. Mixtral 8x7B has 38 scored results on Noometry and o1 has 52.