# Gemini 2.5 Pro vs Mixtral 8x22B

> Gemini 2.5 Pro is the stronger model overall, scoring 44.9 to 26.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gemini-2-5-pro-vs-mixtral-8x22b
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. Gemini 2.5 Pro scores higher in 9 categories and Mixtral 8x22B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Gemini 2.5 Pro leads 55.8 to 15.1.
- The biggest single-benchmark swing is MATH Level 5: 95.9% for Gemini 2.5 Pro and 24.2% for Mixtral 8x22B.
- Mixtral 8x22B is cheaper at $2 / $6 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
- Gemini 2.5 Pro accepts more context: 1.05M tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| Provider | Google | Mistral AI |
| Noometry Index | 44.9 | 26.7 |
| Rank | 67 | 330 |
| Context | 1.05M | 64K |
| Input $/M | $1.25 | $2 |
| Output $/M | $10 | $6 |
| Weights | Proprietary | Open |

## Coding

- Gemini 2.5 Pro: 42.8 (#86)
- Mixtral 8x22B: 23.8 (#324)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| WeirdML | 54% | 3.2% |
| LMArena Coding | 1452 | 1166 |
| SWE-bench Verified | 57.6% | — |
| SWE-bench Verified (bash only) | 53.6% | — |
| Aider Polyglot | 83.1% | — |
| LMArena WebDev | 1227 | — |
| SciCode | 42.8% | — |
| GSO | 3.9% | — |
| BigCodeBench Instruct | — | 40.6% |
| LiveBench Coding | 85.9% | — |
| BigCodeBench Complete | — | 50.2% |
| CadEval | 64% | — |
| ALE-Bench | 785.52 | — |
| AlgoTune | 1.51 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 64.3% |

## Agentic & Tool Use

- Gemini 2.5 Pro: 29.1 (#81)
- Mixtral 8x22B: 22.8 (#119)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| Terminal-Bench | 32.6% | — |
| GDPval | 23.3% | — |
| Remote Labor Index | 0.8% | — |
| TheAgentCompany | 30.3% | — |
| τ²-bench Banking | 13.7% | — |
| Cybench | — | 7.5% |
| DeepResearch Bench | 42.8% | — |
| BALROG | 43.3% | — |
| LMArena Search | 1142 | — |
| METR Time Horizons | 55.4% | — |
| Vending-Bench 2 | 573.64 | — |

## Reasoning

- Gemini 2.5 Pro: 28.8 (#85)
- Mixtral 8x22B: 19.1 (#246)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1455 | 1150 |
| DTBench | 82.4% | 55.1% |
| Epoch Capabilities Index | 145.32 | 122 |
| ForecastBench | 61.3 | 56.3 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 62.4% | — |
| Kagi LLM Benchmark | 70.3% | — |
| ARC-AGI-1 | 41% | — |
| CritPt | 2% | — |
| Chess Puzzles | 20% | — |
| EnigmaEval | 5.6% | — |
| LiveBench Reasoning | 89.8% | — |
| LiveBench Data Analysis | 79.9% | — |
| LMCA | 34.8% | — |
| LiveBench | 82.3% | — |

## Math

- Gemini 2.5 Pro: 31.9 (#191)
- Mixtral 8x22B: 21.2 (#271)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| Omni-MATH | 41.6% | 16.3% |
| LMArena Math | 1450 | 1184 |
| MATH Level 5 | 95.9% | 24.2% |
| FrontierMath (Tiers 1-3) | 24.6% | — |
| FrontierMath Tier 4 | 0% | — |
| OTIS Mock AIME 2024-2025 | 84.7% | — |
| LiveBench Math | 90.2% | — |
| FrontierMath (Feb 2025 set) | 14.1% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Gemini 2.5 Pro: 55.8 (#41)
- Mixtral 8x22B: 15.1 (#288)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| GPQA Diamond | 85.3% | 34.1% |
| MMLU-Pro | 86.3% | 46% |
| GPQA (HELM) | 74.9% | 33.4% |
| LMArena Expert | 1452 | 1113 |
| Humanity's Last Exam | 21.6% | — |
| Confabulations | 10.6% | — |
| Vectara Hallucination Rate | 7% | — |
| MMLU | — | 77.8% |

## Multimodal

- Gemini 2.5 Pro: 44.5 (#16)
- Mixtral 8x22B: —

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| LMArena Vision | 1263 | — |
| GeoBench | 86% | — |
| VPCT | 48% | — |
| LMArena Document | 1421 | — |
| SpatialViz-Bench | 44.7% | — |

## Multilingual

- Gemini 2.5 Pro: 55.5 (#30)
- Mixtral 8x22B: 32.9 (#250)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1452 | 1128 |
| LMArena Chinese | 1507 | 1116 |
| LMArena French | 1473 | 1165 |
| LMArena German | 1487 | 1141 |
| LMArena Japanese | 1462 | 1037 |
| LMArena Korean | 1435 | 1056 |
| LMArena Russian | 1460 | 1158 |
| LMArena Spanish | 1473 | 1150 |

## Instruction Following

- Gemini 2.5 Pro: 75.2 (#71)
- Mixtral 8x22B: 57.9 (#261)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| IFEval | 84% | 72.4% |
| LMArena Instruction Following | 1436 | 1147 |
| LiveBench Instruction Following | 80.6% | — |

## Long Context

- Gemini 2.5 Pro: 59.7 (#5)
- Mixtral 8x22B: 34.6 (#242)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1449 | 1144 |
| Fiction.LiveBench | 91.7% | — |

## Writing & Preference

- Gemini 2.5 Pro: 63.9 (#60)
- Mixtral 8x22B: 37.1 (#257)

| Benchmark | Gemini 2.5 Pro | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1458 | 1162 |
| LMArena Creative Writing | 1453 | 1141 |
| WildBench | 85.7% | 71.1% |
| LMArena Multi-Turn | 1453 | 1130 |
| Short-Story Creative Writing | 83.8% | — |
| EQ-Bench Creative Writing | 1421 | — |
| LiveBench Language | 67.8% | — |

## FAQ

### Is Gemini 2.5 Pro better than Mixtral 8x22B?

Gemini 2.5 Pro is the stronger model overall, scoring 44.9 to 26.7 on the Noometry Index.

### Which is cheaper, Gemini 2.5 Pro or Mixtral 8x22B?

Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.

### Is Gemini 2.5 Pro or Mixtral 8x22B better for coding?

Gemini 2.5 Pro scores higher on coding benchmarks: 42.8 versus 23.8 in the Noometry coding category.

### Which has the bigger context window?

Gemini 2.5 Pro does, with 1.05M tokens against 64K.

### How many benchmarks do Gemini 2.5 Pro and Mixtral 8x22B share?

28 benchmarks have published results for both models. Gemini 2.5 Pro has 78 scored results on Noometry and Mixtral 8x22B has 34.