# Grok 4.6 vs Mixtral 8x22B

> Grok 4.6 is the stronger model overall, scoring 56.8 to 26.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/grok-4-6-vs-mixtral-8x22b
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. Grok 4.6 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 Grok 4.6 leads 63.3 to 15.1.
- The biggest single-benchmark swing is WeirdML: 67.3% for Grok 4.6 and 3.2% for Mixtral 8x22B.
- Both cost about the same: $2 input and $6 output per million tokens.
- Grok 4.6 accepts more context: 500K tokens versus 64K.
- Mixtral 8x22B has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 56.8 | 26.7 |
| Rank | 19 | 330 |
| Context | 500K | 64K |
| Input $/M | $2 | $2 |
| Output $/M | $6 | $6 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.6: 58.0 (#14)
- Mixtral 8x22B: 23.8 (#324)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| WeirdML | 67.3% | 3.2% |
| LMArena Coding | 1464 | 1166 |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| LMArena WebDev | 1620 | — |
| FrontierSWE | 25.3% | — |
| SciCode | 56.5% | — |
| BigCodeBench Instruct | — | 40.6% |
| BigCodeBench Complete | — | 50.2% |
| ALE-Bench | 1,508 | — |
| HumanEval+ | — | 72% |
| MBPP+ | — | 64.3% |

## Agentic & Tool Use

- Grok 4.6: 39.4 (#25)
- Mixtral 8x22B: 22.8 (#119)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| APEX-Agents | 65.3% | — |
| Cybench | — | 7.5% |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |

## Reasoning

- Grok 4.6: 61.3 (#18)
- Mixtral 8x22B: 19.1 (#246)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Hard Prompts | 1445 | 1150 |
| DTBench | 97.3% | 55.1% |
| Epoch Capabilities Index | 156.48 | 122 |
| ARC-AGI-2 | 67.1% | — |
| SimpleBench | 75.9% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| CritPt | 19.7% | — |
| Chess Puzzles | 40% | — |
| EBR-Bench | 30.5% | — |
| Mystery Game Puzzles | 34% | — |
| LMCA | 48.5% | — |
| ForecastBench | — | 56.3 |

## Math

- Grok 4.6: 66.8 (#19)
- Mixtral 8x22B: 21.2 (#271)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Math | 1416 | 1184 |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| OTIS Mock AIME 2024-2025 | 99.2% | — |
| ProofBench | 51% | — |
| Omni-MATH | — | 16.3% |
| MATH Level 5 | — | 24.2% |

## Knowledge

- Grok 4.6: 63.3 (#18)
- Mixtral 8x22B: 15.1 (#288)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| GPQA Diamond | 94% | 34.1% |
| LMArena Expert | 1463 | 1113 |
| SimpleQA Verified | 49.3% | — |
| MMLU-Pro | — | 46% |
| GPQA (HELM) | — | 33.4% |
| MMLU | — | 77.8% |

## Multimodal

- Grok 4.6: 43.9 (#18)
- Mixtral 8x22B: —

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Vision | 1265 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |

## Multilingual

- Grok 4.6: 53.3 (#67)
- Mixtral 8x22B: 32.9 (#250)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Non-English | 1422 | 1128 |
| LMArena Chinese | 1479 | 1116 |
| LMArena French | 1458 | 1165 |
| LMArena German | 1425 | 1141 |
| LMArena Japanese | 1383 | 1037 |
| LMArena Korean | 1395 | 1056 |
| LMArena Russian | 1427 | 1158 |
| LMArena Spanish | 1408 | 1150 |

## Instruction Following

- Grok 4.6: 75.6 (#59)
- Mixtral 8x22B: 57.9 (#261)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Instruction Following | 1431 | 1147 |
| IFEval | — | 72.4% |

## Long Context

- Grok 4.6: 44.4 (#62)
- Mixtral 8x22B: 34.6 (#242)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Longer Query | 1453 | 1144 |

## Writing & Preference

- Grok 4.6: 62.5 (#77)
- Mixtral 8x22B: 37.1 (#257)

| Benchmark | Grok 4.6 | Mixtral 8x22B |
|---|---|---|
| LMArena Text | 1427 | 1162 |
| LMArena Creative Writing | 1430 | 1141 |
| LMArena Multi-Turn | 1422 | 1130 |
| WildBench | — | 71.1% |

## FAQ

### Is Grok 4.6 better than Mixtral 8x22B?

Grok 4.6 is the stronger model overall, scoring 56.8 to 26.7 on the Noometry Index.

### Which is cheaper, Grok 4.6 or Mixtral 8x22B?

Mixtral 8x22B is cheaper. It lists at $2 per million input tokens and $6 per million output tokens; Grok 4.6 lists at $2 and $6.

### Is Grok 4.6 or Mixtral 8x22B better for coding?

Grok 4.6 scores higher on coding benchmarks: 58.0 versus 23.8 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.6 does, with 500K tokens against 64K.

### How many benchmarks do Grok 4.6 and Mixtral 8x22B share?

21 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Mixtral 8x22B has 34.