Model comparison

Mistral Small 3.2 vs Qwen2.5-Coder-32B

Qwen2.5-Coder-32B is the stronger model overall, scoring 33.4 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 5.6× less per token, which makes it the better buy when Qwen2.5-Coder-32B's lead doesn't matter for your workload.

Last verified October 11, 2026. 1 shared benchmarks.

Mistral Small 3.2

Mistral AI

31.2

Rank #280 Confirmed

Qwen2.5-Coder-32B

Alibaba (Qwen)

33.4

Rank #245 Confirmed

Summary

They share 1 benchmark with published results for both. Mistral Small 3.2 scores higher in 1 category and Qwen2.5-Coder-32B in 3 categories; 4 gaps are clear of the uncertainty.
The widest gap is in math, where Qwen2.5-Coder-32B leads 33.3 to 26.3.
Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.66 / $1 for Qwen2.5-Coder-32B.
Mistral Small 3.2 accepts more context: 256K tokens versus 33K.

Side by side

Mistral Small 3.2 and Qwen2.5-Coder-32B specifications
	Mistral Small 3.2	Qwen2.5-Coder-32B
Provider	Mistral AI	Alibaba (Qwen)
Noometry Index	31.2	33.4
Released	2025-06-20	2024-09-18
Weights	Open	Open
Context window	256K	33K
Max output	16K	29K
Input $ / M tokens	$0.0938	$0.66
Output $ / M tokens	$0.25	$1
Results tracked	6	31

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Category by category

Coding Not comparable

Mistral Small 3.2: —, Qwen2.5-Coder-32B: 22.6 (#333)

Coding benchmarks
Benchmark	Mistral Small 3.2	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 Small 3.2: 18.1 (#287), Qwen2.5-Coder-32B: 21.2 (#225)

Reasoning benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
Epoch Capabilities Index	131.74	119.49
Kagi LLM Benchmark	40.4%	—
Chess Puzzles	1%	—
LiveBench Reasoning	—	42.1%
LMArena Hard Prompts	—	1251
LiveBench Data Analysis	—	49.9%
HellaSwag	—	83%
LiveBench	—	46.2%
WinoGrande	—	80.8%

Math Qwen2.5-Coder-32B leads

Mistral Small 3.2: 26.3 (#260), Qwen2.5-Coder-32B: 33.3 (#204)

Math benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
OTIS Mock AIME 2024-2025	30.3%	—
LiveBench Math	—	46.6%
LMArena Math	—	1251
GSM8K	—	93%

Knowledge Qwen2.5-Coder-32B leads

Mistral Small 3.2: 26.7 (#256), Qwen2.5-Coder-32B: 33.4 (#203)

Knowledge benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
GPQA Diamond	49.1%	—
LMArena Expert	—	1221
ARC (AI2) Challenge	—	70.5%
MMLU	—	79.1%

Multilingual Not comparable

Mistral Small 3.2: —, Qwen2.5-Coder-32B: 37.8 (#235)

Multilingual benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
LMArena Non-English	—	1205
LMArena Chinese	—	1222
LMArena Russian	—	1228

Instruction Following Not comparable

Mistral Small 3.2: —, Qwen2.5-Coder-32B: 61.4 (#245)

Instruction Following benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
LiveBench Instruction Following	—	58.7%
LMArena Instruction Following	—	1223

Long Context Not comparable

Mistral Small 3.2: —, Qwen2.5-Coder-32B: 38.0 (#208)

Long Context benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
LMArena Longer Query	—	1251

Writing & Preference Mistral Small 3.2 leads

Mistral Small 3.2: 45.0 (#224), Qwen2.5-Coder-32B: 41.6 (#240)

Writing & Preference benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5-Coder-32B
LMArena Text	—	1230
LMArena Creative Writing	—	1174
EQ-Bench Creative Writing	1255	—
LMArena Multi-Turn	—	1222
LiveBench Language	—	23.3%

Frequently asked questions

Is Mistral Small 3.2 better than Qwen2.5-Coder-32B?

Which is cheaper, Mistral Small 3.2 or Qwen2.5-Coder-32B?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; Qwen2.5-Coder-32B lists at $0.66 and $1.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 33K.

How many benchmarks do Mistral Small 3.2 and Qwen2.5-Coder-32B share?

1 benchmark has published results for both models. Mistral Small 3.2 has 6 scored results on Noometry and Qwen2.5-Coder-32B has 31.