Model comparison

Mistral Small 3.2 vs Qwen2.5 7B Instruct

Mistral Small 3.2 is the stronger model overall, scoring 31.2 to 29.0 on the Noometry Index.

Last verified October 12, 2026. 4 shared benchmarks.

Mistral Small 3.2

Mistral AI

31.2

Rank #280 Confirmed

Qwen2.5 7B Instruct

Alibaba (Qwen)

29.0

Rank #320 Confirmed

Summary

They share 4 benchmarks with published results for both. Mistral Small 3.2 scores higher in 3 categories and Qwen2.5 7B Instruct in 1 category; 4 gaps are clear of the uncertainty.
The widest gap is in math, where Mistral Small 3.2 leads 26.3 to 12.6.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 30.3% for Mistral Small 3.2 and 2.5% for Qwen2.5 7B Instruct.
Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.17 / $0.70 for Qwen2.5 7B Instruct.
Mistral Small 3.2 accepts more context: 256K tokens versus 131K.

Side by side

Mistral Small 3.2 and Qwen2.5 7B Instruct specifications
	Mistral Small 3.2	Qwen2.5 7B Instruct
Provider	Mistral AI	Alibaba (Qwen)
Noometry Index	31.2	29.0
Released	2025-06-20	2024-09
Weights	Open	Open
Context window	256K	131K
Max output	16K	8K
Input $ / M tokens	$0.0938	$0.17
Output $ / M tokens	$0.25	$0.70
Results tracked	6	15

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Category by category

Coding Not comparable

Mistral Small 3.2: —, Qwen2.5 7B Instruct: 36.5 (#208)

Coding benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
BigCodeBench Instruct	—	37.6%
BigCodeBench Complete	—	46.1%

Agentic & Tool Use Not comparable

Mistral Small 3.2: —, Qwen2.5 7B Instruct: 23.8 (#124)

Agentic & Tool Use benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
BALROG	—	7.8%

Reasoning Mistral Small 3.2 leads

Mistral Small 3.2: 18.1 (#287), Qwen2.5 7B Instruct: 14.8 (#322)

Reasoning benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
Chess Puzzles	1%	0%
Epoch Capabilities Index	131.74	118.51
Kagi LLM Benchmark	40.4%	—
DTBench	—	47.7%
LMCA	—	6.4%

Math Mistral Small 3.2 leads

Mistral Small 3.2: 26.3 (#260), Qwen2.5 7B Instruct: 12.6 (#306)

Math benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
OTIS Mock AIME 2024-2025	30.3%	2.5%
Omni-MATH	—	29.4%

Knowledge Mistral Small 3.2 leads

Mistral Small 3.2: 26.7 (#256), Qwen2.5 7B Instruct: 17.0 (#286)

Knowledge benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
GPQA Diamond	49.1%	35.5%
MMLU-Pro	—	53.9%
GPQA (HELM)	—	34.1%
MMLU	—	72.9%

Instruction Following Not comparable

Mistral Small 3.2: —, Qwen2.5 7B Instruct: 63.2 (#231)

Instruction Following benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
IFEval	—	74.1%

Writing & Preference Qwen2.5 7B Instruct leads

Mistral Small 3.2: 45.0 (#224), Qwen2.5 7B Instruct: 48.8 (#195)

Writing & Preference benchmarks
Benchmark	Mistral Small 3.2	Qwen2.5 7B Instruct
EQ-Bench Creative Writing	1255	—
WildBench	—	73.1%

Frequently asked questions

Is Mistral Small 3.2 better than Qwen2.5 7B Instruct?

Mistral Small 3.2 is the stronger model overall, scoring 31.2 to 29.0 on the Noometry Index.

Which is cheaper, Mistral Small 3.2 or Qwen2.5 7B Instruct?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; Qwen2.5 7B Instruct lists at $0.17 and $0.70.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 131K.

How many benchmarks do Mistral Small 3.2 and Qwen2.5 7B Instruct share?

4 benchmarks have published results for both models. Mistral Small 3.2 has 6 scored results on Noometry and Qwen2.5 7B Instruct has 15.