Model comparison

Mistral Medium 3.1 vs Qwen2.5-Coder-32B

Qwen2.5-Coder-32B is the stronger model overall, scoring 33.4 to 31.9 on the Noometry Index.

Last verified October 11, 2026. 0 shared benchmarks.

Mistral Medium 3.1

Mistral AI

31.9

Rank #266 Reported

Qwen2.5-Coder-32B

Alibaba (Qwen)

33.4

Rank #245 Confirmed

Summary

The widest gap is in writing & preference, where Mistral Medium 3.1 leads 55.5 to 41.6.
Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
Mistral Medium 3.1 accepts more context: 131K tokens versus 33K.
Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.

Side by side

Mistral Medium 3.1 and Qwen2.5-Coder-32B specifications
	Mistral Medium 3.1	Qwen2.5-Coder-32B
Provider	Mistral AI	Alibaba (Qwen)
Noometry Index	31.9	33.4
Released	—	2024-09-18
Weights	Proprietary	Open
Context window	131K	33K
Max output	105K	29K
Input $ / M tokens	$0.40	$0.66
Output $ / M tokens	$2	$1
Results tracked	3	31

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Category by category

Coding Not comparable

Mistral Medium 3.1: —, Qwen2.5-Coder-32B: 22.6 (#333)

Coding benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
SWE-bench Verified (bash only)	—	9%
Aider Polyglot	—	16.4%
BigCodeBench Instruct	—	49%
LiveBench Coding	—	56.9%
LMArena Coding	—	1276
BigCodeBench Complete	—	58%
HumanEval+	—	87.2%
MBPP+	—	77%

Reasoning Qwen2.5-Coder-32B leads

Mistral Medium 3.1: 10.6 (#341), Qwen2.5-Coder-32B: 21.2 (#225)

Reasoning benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
NYT Connections (extended)	6.5%	—
Thematic Generalization	20.3%	—
LiveBench Reasoning	—	42.1%
LMArena Hard Prompts	—	1251
LiveBench Data Analysis	—	49.9%
Epoch Capabilities Index	—	119.49
HellaSwag	—	83%
LiveBench	—	46.2%
WinoGrande	—	80.8%

Math Not comparable

Mistral Medium 3.1: —, Qwen2.5-Coder-32B: 33.3 (#204)

Math benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
LiveBench Math	—	46.6%
LMArena Math	—	1251
GSM8K	—	93%

Knowledge Not comparable

Mistral Medium 3.1: —, Qwen2.5-Coder-32B: 33.4 (#203)

Knowledge benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
LMArena Expert	—	1221
ARC (AI2) Challenge	—	70.5%
MMLU	—	79.1%

Multilingual Not comparable

Mistral Medium 3.1: —, Qwen2.5-Coder-32B: 37.8 (#235)

Multilingual benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
LMArena Non-English	—	1205
LMArena Chinese	—	1222
LMArena Russian	—	1228

Instruction Following Not comparable

Mistral Medium 3.1: —, Qwen2.5-Coder-32B: 61.4 (#245)

Instruction Following benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
LiveBench Instruction Following	—	58.7%
LMArena Instruction Following	—	1223

Long Context Not comparable

Mistral Medium 3.1: —, Qwen2.5-Coder-32B: 38.0 (#208)

Long Context benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
LMArena Longer Query	—	1251

Writing & Preference Mistral Medium 3.1 leads

Mistral Medium 3.1: 55.5 (#145), Qwen2.5-Coder-32B: 41.6 (#240)

Writing & Preference benchmarks
Benchmark	Mistral Medium 3.1	Qwen2.5-Coder-32B
LMArena Text	—	1230
LMArena Creative Writing	—	1174
EQ-Bench Creative Writing	1476	—
LMArena Multi-Turn	—	1222
LiveBench Language	—	23.3%

Frequently asked questions

Is Mistral Medium 3.1 better than Qwen2.5-Coder-32B?

Qwen2.5-Coder-32B is the stronger model overall, scoring 33.4 to 31.9 on the Noometry Index.

Which is cheaper, Mistral Medium 3.1 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 Medium 3.1 lists at $0.40 and $2.

Which has the bigger context window?

Mistral Medium 3.1 does, with 131K tokens against 33K.

How many benchmarks do Mistral Medium 3.1 and Qwen2.5-Coder-32B share?

0 benchmarks have published results for both models. Mistral Medium 3.1 has 3 scored results on Noometry and Qwen2.5-Coder-32B has 31.