Noometry

Model comparison

Mistral Large 4 vs Qwen2.5-Coder-32B

Mistral Large 4 is the stronger model overall, scoring 43.1 to 33.4 on the Noometry Index.

Last verified . 12 shared benchmarks.

Mistral Large 4 Mistral AI

43.1

Rank #99 Confirmed

Qwen2.5-Coder-32B Alibaba (Qwen)

33.4

Rank #245 Confirmed

Summary

  • They share 12 benchmarks with published results for both. Mistral Large 4 scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in coding, where Mistral Large 4 leads 48.6 to 22.6.
  • Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $0.68 / $2.09 for Mistral Large 4.
  • Mistral Large 4 accepts more context: 1.05M tokens versus 33K.
  • Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

Side by side

Mistral Large 4Qwen2.5-Coder-32B
ProviderMistral AIAlibaba (Qwen)
Noometry Index43.133.4
Released2026-10-062024-09-18
WeightsProprietaryOpen
Context window1.05M33K
Max output262K29K
Input $ / M tokens$0.68$0.66
Output $ / M tokens$2.09$1
Results tracked1531

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Category by category

Coding Mistral Large 4 leads

Mistral Large 4: 48.6 (#57), Qwen2.5-Coder-32B: 22.6 (#333)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Coding14751276
SWE-bench Verified (bash only)—9%
Aider Polyglot—16.4%
LMArena WebDev1541—
BigCodeBench Instruct—49%
LiveBench Coding—56.9%
BigCodeBench Complete—58%
HumanEval+—87.2%
MBPP+—77%

Reasoning Mistral Large 4 leads

Mistral Large 4: 22.5 (#192), Qwen2.5-Coder-32B: 21.2 (#225)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Hard Prompts14441251
NYT Connections (extended)27.4%—
LiveBench Reasoning—42.1%
LiveBench Data Analysis—49.9%
Epoch Capabilities Index—119.49
HellaSwag—83%
LiveBench—46.2%
WinoGrande—80.8%

Math Mistral Large 4 leads

Mistral Large 4: 40.4 (#91), Qwen2.5-Coder-32B: 33.3 (#204)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Math14881251
LiveBench Math—46.6%
GSM8K—93%

Knowledge Mistral Large 4 leads

Mistral Large 4: 36.6 (#166), Qwen2.5-Coder-32B: 33.4 (#203)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Expert14471221
SimpleQA Verified20%—
ARC (AI2) Challenge—70.5%
MMLU—79.1%

Multilingual Mistral Large 4 leads

Mistral Large 4: 52.6 (#82), Qwen2.5-Coder-32B: 37.8 (#235)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Non-English14151205
LMArena Chinese14911222
LMArena Russian14141228

Instruction Following Mistral Large 4 leads

Mistral Large 4: 75.0 (#76), Qwen2.5-Coder-32B: 61.4 (#245)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Instruction Following14241223
LiveBench Instruction Following—58.7%

Long Context Mistral Large 4 leads

Mistral Large 4: 43.6 (#89), Qwen2.5-Coder-32B: 38.0 (#208)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Longer Query14291251

Writing & Preference Mistral Large 4 leads

Mistral Large 4: 60.4 (#97), Qwen2.5-Coder-32B: 41.6 (#240)

BenchmarkMistral Large 4Qwen2.5-Coder-32B
LMArena Text14271230
LMArena Creative Writing13611174
LMArena Multi-Turn14241222
LiveBench Language—23.3%

Frequently asked questions

Is Mistral Large 4 better than Qwen2.5-Coder-32B?

Mistral Large 4 is the stronger model overall, scoring 43.1 to 33.4 on the Noometry Index.

Which is cheaper, Mistral Large 4 or Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; Mistral Large 4 lists at $0.68 and $2.09.

Is Mistral Large 4 or Qwen2.5-Coder-32B better for coding?

Mistral Large 4 scores higher on coding benchmarks: 48.6 versus 22.6 in the Noometry coding category.

Which has the bigger context window?

Mistral Large 4 does, with 1.05M tokens against 33K.

How many benchmarks do Mistral Large 4 and Qwen2.5-Coder-32B share?

12 benchmarks have published results for both models. Mistral Large 4 has 15 scored results on Noometry and Qwen2.5-Coder-32B has 31.

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