Model comparison

GLM-4.5 vs Mistral Small 3.2

GLM-4.5 is the stronger model overall, scoring 42.0 to 31.2 on the Noometry Index. Mistral Small 3.2 costs 7.5× less per token, which makes it the better buy when GLM-4.5's lead doesn't matter for your workload.

Last verified October 10, 2026. 2 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

Mistral Small 3.2

Mistral AI

31.2

Rank #280 Confirmed

Summary

They share 2 benchmarks with published results for both. GLM-4.5 scores higher in 4 categories and Mistral Small 3.2 in 0 categories; 4 gaps are clear of the uncertainty.
The widest gap is in math, where GLM-4.5 leads 39.0 to 26.3.
The biggest single-benchmark swing is Kagi LLM Benchmark: 57.9% for GLM-4.5 and 40.4% for Mistral Small 3.2.
Mistral Small 3.2 is cheaper at $0.0938 / $0.25 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
Mistral Small 3.2 accepts more context: 256K tokens versus 131K.

Side by side

GLM-4.5 and Mistral Small 3.2 specifications
	GLM-4.5	Mistral Small 3.2
Provider	Z.ai (Zhipu)	Mistral AI
Noometry Index	42.0	31.2
Released	2025-07-27	2025-06-20
Weights	Open	Open
Context window	131K	256K
Max output	98K	16K
Input $ / M tokens	$0.60	$0.0938
Output $ / M tokens	$2.20	$0.25
Results tracked	27	6

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Category by category

Coding Not comparable

GLM-4.5: 41.4 (#125), Mistral Small 3.2: —

Coding benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
SWE-bench Verified (bash only)	54.2%	—
WeirdML	40.6%	—
LMArena Coding	1434	—
ALE-Bench	344.82	—
AlgoTune	1.52	—

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), Mistral Small 3.2: 18.1 (#287)

Reasoning benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
Kagi LLM Benchmark	57.9%	40.4%
Chess Puzzles	—	1%
LMArena Hard Prompts	1429	—
Epoch Capabilities Index	—	131.74

Math GLM-4.5 leads

GLM-4.5: 39.0 (#116), Mistral Small 3.2: 26.3 (#260)

Math benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
OTIS Mock AIME 2024-2025	—	30.3%
LMArena Math	1427	—

Knowledge GLM-4.5 leads

GLM-4.5: 35.9 (#179), Mistral Small 3.2: 26.7 (#256)

Knowledge benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
GPQA Diamond	—	49.1%
Humanity's Last Exam	8.3%	—
Confabulations	11.3%	—
LMArena Expert	1433	—

Multilingual Not comparable

GLM-4.5: 52.8 (#77), Mistral Small 3.2: —

Multilingual benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
LMArena Non-English	1417	—
LMArena Chinese	1465	—
LMArena French	1418	—
LMArena German	1407	—
LMArena Japanese	1415	—
LMArena Korean	1380	—
LMArena Russian	1414	—
LMArena Spanish	1454	—

Instruction Following Not comparable

GLM-4.5: 74.1 (#104), Mistral Small 3.2: —

Instruction Following benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
LMArena Instruction Following	1404	—

Long Context Not comparable

GLM-4.5: 38.2 (#201), Mistral Small 3.2: —

Long Context benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
Fiction.LiveBench	58.3%	—
LMArena Longer Query	1412	—

Writing & Preference GLM-4.5 leads

GLM-4.5: 57.5 (#127), Mistral Small 3.2: 45.0 (#224)

Writing & Preference benchmarks
Benchmark	GLM-4.5	Mistral Small 3.2
EQ-Bench Creative Writing	1343	1255
LMArena Text	1430	—
LMArena Creative Writing	1395	—
Short-Story Creative Writing	73.4%	—
LMArena Multi-Turn	1415	—

Frequently asked questions

Is GLM-4.5 better than Mistral Small 3.2?

Which is cheaper, GLM-4.5 or Mistral Small 3.2?

Mistral Small 3.2 is cheaper. It lists at $0.0938 per million input tokens and $0.25 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

Which has the bigger context window?

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

How many benchmarks do GLM-4.5 and Mistral Small 3.2 share?

2 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Mistral Small 3.2 has 6.