# Mistral Large vs Qwen3.6 Plus

> Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/mistral-large-vs-qwen3-6-plus
- Last updated: 2026-10-11
- Shared benchmarks: 26

## Summary

- They share 26 benchmarks with published results for both. Mistral Large scores higher in 0 categories and Qwen3.6 Plus in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.6 Plus leads 51.8 to 18.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 8.5% for Mistral Large and 93.3% for Qwen3.6 Plus.
- Qwen3.6 Plus is cheaper at $0.50 / $3 per million input/output tokens, against $2 / $6 for Mistral Large.
- Qwen3.6 Plus accepts more context: 1M tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.

## Snapshot

| | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen) |
| Noometry Index | 31.9 | 47.5 |
| Rank | 263 | 62 |
| Context | 131K | 1M |
| Input $/M | $2 | $0.50 |
| Output $/M | $6 | $3 |
| Weights | Open | Proprietary |

## Coding

- Mistral Large: 34.3 (#240)
- Qwen3.6 Plus: 40.8 (#130)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| SciCode | 36.2% | 40.7% |
| LMArena Coding | 1277 | 1467 |
| ALE-Bench | 264.7 | 670.15 |
| SWE-bench Verified | — | 57.9% |
| LMArena WebDev | — | 1461 |
| BigCodeBench Instruct | 30% | — |
| LiveBench Coding | 47.1% | — |
| BigCodeBench Complete | 38.3% | — |
| HumanEval+ | 62.2% | — |
| MBPP+ | 59.5% | — |

## Agentic & Tool Use

- Mistral Large: 28.6 (#89)
- Qwen3.6 Plus: —

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| Berkeley Function Calling Leaderboard | 38.4% | — |
| Vending-Bench 2 | — | 5,115 |

## Reasoning

- Mistral Large: 15.8 (#310)
- Qwen3.6 Plus: 29.3 (#93)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| CritPt | 0% | 2.9% |
| LMArena Hard Prompts | 1257 | 1449 |
| DTBench | 65.1% | 81.9% |
| LMCA | 16.7% | 33.1% |
| Epoch Capabilities Index | 128.52 | 147.65 |
| SimpleBench | 22.5% | — |
| NYT Connections (extended) | — | 60.3% |
| Chess Puzzles | — | 17% |
| Thematic Generalization | — | 59.5% |
| LiveBench Reasoning | 43.5% | — |
| Mystery Game Puzzles | — | 12% |
| LiveBench Data Analysis | 50.1% | — |
| ForecastBench | 57.1 | — |
| LiveBench | 48.4% | — |

## Math

- Mistral Large: 18.2 (#291)
- Qwen3.6 Plus: 51.8 (#54)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.5% | 93.3% |
| LMArena Math | 1262 | 1450 |
| FrontierMath (Feb 2025 set) | 0.3% | 26.2% |
| FrontierMath (Tiers 1-3) | — | 38.2% |
| Omni-MATH | 28.1% | — |
| LiveBench Math | 42.5% | — |
| MATH Level 5 | 50.3% | — |
| FrontierMath Tier 4 (v1) | — | 8.3% |

## Knowledge

- Mistral Large: 30.1 (#230)
- Qwen3.6 Plus: 56.1 (#45)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| GPQA Diamond | 51.3% | 88.4% |
| LMArena Expert | 1232 | 1454 |
| SimpleQA Verified | — | 44.1% |
| MMLU-Pro | 59.9% | — |
| Confabulations | 21.4% | — |
| Vectara Hallucination Rate | 4.5% | — |
| GPQA (HELM) | 43.5% | — |
| MMLU | 80% | — |

## Multilingual

- Mistral Large: 40.0 (#219)
- Qwen3.6 Plus: 53.3 (#70)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| LMArena Non-English | 1237 | 1424 |
| LMArena Chinese | 1240 | 1477 |
| LMArena French | 1325 | 1455 |
| LMArena German | 1254 | 1452 |
| LMArena Japanese | 1188 | 1389 |
| LMArena Korean | 1202 | 1379 |
| LMArena Russian | 1257 | 1434 |
| LMArena Spanish | 1268 | 1432 |

## Instruction Following

- Mistral Large: 67.9 (#191)
- Qwen3.6 Plus: 75.0 (#74)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| LMArena Instruction Following | 1249 | 1425 |
| LiveBench Instruction Following | 67.9% | — |
| IFEval | 87.7% | — |

## Long Context

- Mistral Large: 38.3 (#199)
- Qwen3.6 Plus: 45.2 (#49)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| LMArena Longer Query | 1261 | 1439 |
| CL-bench | — | 20.3% |

## Writing & Preference

- Mistral Large: 40.7 (#242)
- Qwen3.6 Plus: 62.2 (#82)

| Benchmark | Mistral Large | Qwen3.6 Plus |
|---|---|---|
| LMArena Text | 1266 | 1437 |
| LMArena Creative Writing | 1243 | 1404 |
| LMArena Multi-Turn | 1260 | 1438 |
| Short-Story Creative Writing | 69% | — |
| EQ-Bench Creative Writing | 985 | — |
| WildBench | 80.1% | — |
| LiveBench Language | 39.4% | — |

## FAQ

### Is Mistral Large better than Qwen3.6 Plus?

Qwen3.6 Plus is the stronger model overall, scoring 47.5 to 31.9 on the Noometry Index.

### Which is cheaper, Mistral Large or Qwen3.6 Plus?

Qwen3.6 Plus is cheaper. It lists at $0.50 per million input tokens and $3 per million output tokens; Mistral Large lists at $2 and $6.

### Is Mistral Large or Qwen3.6 Plus better for coding?

Qwen3.6 Plus scores higher on coding benchmarks: 40.8 versus 34.3 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.6 Plus does, with 1M tokens against 131K.

### How many benchmarks do Mistral Large and Qwen3.6 Plus share?

26 benchmarks have published results for both models. Mistral Large has 51 scored results on Noometry and Qwen3.6 Plus has 37.