# Grok 4.6 vs Mistral Large

> Grok 4.6 is the stronger model overall, scoring 56.9 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/grok-4-6-vs-mistral-large
- Last updated: 2026-10-10
- Shared benchmarks: 26

## Summary

- They share 26 benchmarks with published results for both. Grok 4.6 scores higher in 9 categories and Mistral Large in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Grok 4.6 leads 67.0 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 99.2% for Grok 4.6 and 8.5% for Mistral Large.
- Both cost about the same: $2 input and $6 output per million tokens.
- Grok 4.6 accepts more context: 500K tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.6 | Mistral Large |
|---|---|---|
| Provider | xAI | Mistral AI |
| Noometry Index | 56.9 | 31.9 |
| Rank | 21 | 263 |
| Context | 500K | 131K |
| Input $/M | $2 | $2 |
| Output $/M | $6 | $6 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.6: 58.5 (#16)
- Mistral Large: 34.3 (#240)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| SciCode | 56.5% | 36.2% |
| LMArena Coding | 1465 | 1277 |
| ALE-Bench | 1,508 | 264.7 |
| DeepSWE | 67.5% | — |
| FrontierCode | 48% | — |
| CursorBench | 41.4% | — |
| LMArena WebDev | 1617 | — |
| FrontierSWE | 25.3% | — |
| WeirdML | 67.3% | — |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| BigCodeBench Complete | — | 38.3% |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |

## Agentic & Tool Use

- Grok 4.6: 39.4 (#27)
- Mistral Large: 28.6 (#89)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| APEX-Agents | 65.3% | — |
| Berkeley Function Calling Leaderboard | — | 38.4% |
| GDP.pdf | 17.2% | — |
| Vending-Bench 2 | 9,047 | — |

## Reasoning

- Grok 4.6: 61.4 (#20)
- Mistral Large: 15.8 (#310)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| SimpleBench | 75.9% | 22.5% |
| CritPt | 19.7% | 0% |
| LMArena Hard Prompts | 1447 | 1257 |
| DTBench | 97.3% | 65.1% |
| LMCA | 48.5% | 16.7% |
| Epoch Capabilities Index | 156.44 | 128.52 |
| ARC-AGI-2 | 67.1% | — |
| NYT Connections (extended) | 80% | — |
| ARC-AGI-1 | 87.5% | — |
| Chess Puzzles | 40% | — |
| EBR-Bench | 30.5% | — |
| LiveBench Reasoning | — | 43.5% |
| Mystery Game Puzzles | 34% | — |
| LiveBench Data Analysis | — | 50.1% |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |

## Math

- Grok 4.6: 67.0 (#24)
- Mistral Large: 18.2 (#291)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 99.2% | 8.5% |
| LMArena Math | 1423 | 1262 |
| FrontierMath (Tiers 1-3) | 66% | — |
| FrontierMath Tier 4 | 31.7% | — |
| ProofBench | 51% | — |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |

## Knowledge

- Grok 4.6: 63.3 (#20)
- Mistral Large: 30.1 (#230)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| GPQA Diamond | 94% | 51.3% |
| LMArena Expert | 1467 | 1232 |
| SimpleQA Verified | 49.3% | — |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| MMLU | — | 80% |

## Multimodal

- Grok 4.6: 43.6 (#23)
- Mistral Large: —

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| LMArena Vision | 1263 | — |
| Blueprint-Bench 2 | 33.2% | — |
| Furniture Assembly | 40% | — |
| LMArena Document | 1452 | — |

## Multilingual

- Grok 4.6: 53.0 (#74)
- Mistral Large: 40.0 (#219)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| LMArena Non-English | 1420 | 1237 |
| LMArena Chinese | 1480 | 1240 |
| LMArena French | 1461 | 1325 |
| LMArena German | 1431 | 1254 |
| LMArena Japanese | 1376 | 1188 |
| LMArena Korean | 1397 | 1202 |
| LMArena Russian | 1422 | 1257 |
| LMArena Spanish | 1404 | 1268 |

## Instruction Following

- Grok 4.6: 75.4 (#63)
- Mistral Large: 67.9 (#191)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| LMArena Instruction Following | 1431 | 1249 |
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |

## Long Context

- Grok 4.6: 44.5 (#66)
- Mistral Large: 38.3 (#199)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| LMArena Longer Query | 1454 | 1261 |

## Writing & Preference

- Grok 4.6: 62.3 (#80)
- Mistral Large: 40.7 (#242)

| Benchmark | Grok 4.6 | Mistral Large |
|---|---|---|
| LMArena Text | 1428 | 1266 |
| LMArena Creative Writing | 1428 | 1243 |
| LMArena Multi-Turn | 1425 | 1260 |
| Short-Story Creative Writing | — | 69% |
| EQ-Bench Creative Writing | — | 985 |
| WildBench | — | 80.1% |
| LiveBench Language | — | 39.4% |

## FAQ

### Is Grok 4.6 better than Mistral Large?

Grok 4.6 is the stronger model overall, scoring 56.9 to 31.9 on the Noometry Index.

### Which is cheaper, Grok 4.6 or Mistral Large?

Mistral Large 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 Mistral Large better for coding?

Grok 4.6 scores higher on coding benchmarks: 58.5 versus 34.3 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.6 does, with 500K tokens against 131K.

### How many benchmarks do Grok 4.6 and Mistral Large share?

26 benchmarks have published results for both models. Grok 4.6 has 49 scored results on Noometry and Mistral Large has 51.