Noometry

Model comparison

Mistral vs Qwen3 235B-A22B

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 29.9 on the Noometry Index.

Last verified . 22 shared benchmarks.

Mistral Mistral AI

29.9

Rank #303 Confirmed

Qwen3 235B-A22B Alibaba (Qwen)

43.5

Rank #91 Confirmed

Summary

  • They share 22 benchmarks with published results for both. Mistral scores higher in 1 category and Qwen3 235B-A22B in 7 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3 235B-A22B leads 49.6 to 16.6.
  • The biggest single-benchmark swing is Omni-MATH: 7.2% for Mistral and 71.8% for Qwen3 235B-A22B.
  • Qwen3 235B-A22B has downloadable open weights; the other is API-only.

Side by side

MistralQwen3 235B-A22B
ProviderMistral AIAlibaba (Qwen)
Noometry Index29.943.5
Released—2025-04
WeightsProprietaryOpen
Context window—131K
Max output—16K
Input $ / M tokens—$0.70
Output $ / M tokens—$2.80
Results tracked2249

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Category by category

Coding Qwen3 235B-A22B leads

Mistral: 33.8 (#250), Qwen3 235B-A22B: 44.3 (#75)

BenchmarkMistralQwen3 235B-A22B
LMArena Coding11621445
Aider Polyglot—59.6%
SciCode—42.4%
WeirdML—41%

Agentic & Tool Use Not comparable

Mistral: —, Qwen3 235B-A22B: 33.9 (#51)

BenchmarkMistralQwen3 235B-A22B
Berkeley Function Calling Leaderboard—52.1%
Vending-Bench 2—-11.34

Reasoning Mistral leads

Mistral: 22.2 (#200), Qwen3 235B-A22B: 15.7 (#311)

BenchmarkMistralQwen3 235B-A22B
LMArena Hard Prompts11491433
ARC-AGI-2—1.3%
SimpleBench—31%
Kagi LLM Benchmark—69.4%
ARC-AGI-1—11%
CritPt—0%
Chess Puzzles—12%
Mystery Game Puzzles—9%
DTBench—80.3%
LMCA—29.3%
Epoch Capabilities Index—143.85
ForecastBench—59.7

Math Qwen3 235B-A22B leads

Mistral: 22.3 (#278), Qwen3 235B-A22B: 50.4 (#57)

BenchmarkMistralQwen3 235B-A22B
Omni-MATH7.2%71.8%
LMArena Math11801432
OTIS Mock AIME 2024-2025—86.7%
MATH Level 5—68.9%
FrontierMath (Feb 2025 set)—8.5%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3 235B-A22B leads

Mistral: 16.6 (#288), Qwen3 235B-A22B: 49.6 (#73)

BenchmarkMistralQwen3 235B-A22B
MMLU-Pro27.7%84.4%
GPQA (HELM)30.3%72.7%
LMArena Expert11251463
GPQA Diamond—80.1%
SimpleQA Verified—40.4%
Confabulations—15.6%
Vectara Hallucination Rate—9.3%

Multilingual Qwen3 235B-A22B leads

Mistral: 32.8 (#254), Qwen3 235B-A22B: 52.3 (#89)

BenchmarkMistralQwen3 235B-A22B
LMArena Non-English11291409
LMArena Chinese11091481
LMArena French11801445
LMArena German11551433
LMArena Japanese10131399
LMArena Korean10321391
LMArena Russian11681411
LMArena Spanish11431430

Instruction Following Qwen3 235B-A22B leads

Mistral: 52.6 (#288), Qwen3 235B-A22B: 72.6 (#136)

BenchmarkMistralQwen3 235B-A22B
IFEval56.8%83.5%
LMArena Instruction Following11521408

Long Context Qwen3 235B-A22B leads

Mistral: 35.0 (#245), Qwen3 235B-A22B: 46.1 (#26)

BenchmarkMistralQwen3 235B-A22B
LMArena Longer Query11531426
Fiction.LiveBench—75%

Writing & Preference Qwen3 235B-A22B leads

Mistral: 37.0 (#260), Qwen3 235B-A22B: 59.6 (#108)

BenchmarkMistralQwen3 235B-A22B
LMArena Text11651419
LMArena Creative Writing11581384
WildBench66%86.6%
LMArena Multi-Turn11471432
Short-Story Creative Writing—83%
EQ-Bench Creative Writing—1366

Frequently asked questions

Is Mistral better than Qwen3 235B-A22B?

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 29.9 on the Noometry Index.

Is Mistral or Qwen3 235B-A22B better for coding?

Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 33.8 in the Noometry coding category.

How many benchmarks do Mistral and Qwen3 235B-A22B share?

22 benchmarks have published results for both models. Mistral has 22 scored results on Noometry and Qwen3 235B-A22B has 49.

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