Noometry

Model comparison

GLM-4.6 vs Mistral Small 3.2

GLM-4.6 is the stronger model overall, scoring 41.4 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-4.6's lead doesn't matter for your workload.

Last verified . 2 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Mistral Small 3.2 Mistral AI

31.2

Rank #280 Confirmed

Summary

  • They share 2 benchmarks with published results for both. GLM-4.6 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 writing & preference, where GLM-4.6 leads 61.1 to 45.0.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 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-4.6.
  • Mistral Small 3.2 accepts more context: 256K tokens versus 205K.

Side by side

GLM-4.6Mistral Small 3.2
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index41.431.2
Released2025-09-302025-06-20
WeightsOpenOpen
Context window205K256K
Max output131K16K
Input $ / M tokens$0.60$0.0938
Output $ / M tokens$2.20$0.25
Results tracked296

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Category by category

Coding Not comparable

GLM-4.6: 40.1 (#148), Mistral Small 3.2: —

BenchmarkGLM-4.6Mistral Small 3.2
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1340—
SciCode38.4%—
LMArena Coding1449—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Mistral Small 3.2: —

BenchmarkGLM-4.6Mistral Small 3.2
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.7 (#172), Mistral Small 3.2: 18.1 (#287)

BenchmarkGLM-4.6Mistral Small 3.2
Kagi LLM Benchmark47.4%40.4%
CritPt1.1%—
Chess Puzzles—1%
LMArena Hard Prompts1440—
Epoch Capabilities Index—131.74

Math GLM-4.6 leads

GLM-4.6: 39.1 (#111), Mistral Small 3.2: 26.3 (#260)

BenchmarkGLM-4.6Mistral Small 3.2
OTIS Mock AIME 2024-2025—30.3%
LMArena Math1432—
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 40.2 (#124), Mistral Small 3.2: 26.7 (#256)

BenchmarkGLM-4.6Mistral Small 3.2
GPQA Diamond—49.1%
Vectara Hallucination Rate9.5%—
LMArena Expert1431—

Multilingual Not comparable

GLM-4.6: 53.5 (#66), Mistral Small 3.2: —

BenchmarkGLM-4.6Mistral Small 3.2
LMArena Non-English1426—
LMArena Chinese1499—
LMArena French1459—
LMArena German1447—
LMArena Japanese1393—
LMArena Korean1400—
LMArena Russian1419—
LMArena Spanish1436—

Instruction Following Not comparable

GLM-4.6: 74.3 (#98), Mistral Small 3.2: —

BenchmarkGLM-4.6Mistral Small 3.2
LMArena Instruction Following1410—

Long Context Not comparable

GLM-4.6: 43.4 (#94), Mistral Small 3.2: —

BenchmarkGLM-4.6Mistral Small 3.2
LMArena Longer Query1422—

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Mistral Small 3.2: 45.0 (#224)

BenchmarkGLM-4.6Mistral Small 3.2
EQ-Bench Creative Writing14111255
LMArena Text1440—
LMArena Creative Writing1411—
LMArena Multi-Turn1427—

Frequently asked questions

Is GLM-4.6 better than Mistral Small 3.2?

GLM-4.6 is the stronger model overall, scoring 41.4 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-4.6's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6 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-4.6 lists at $0.60 and $2.20.

Which has the bigger context window?

Mistral Small 3.2 does, with 256K tokens against 205K.

How many benchmarks do GLM-4.6 and Mistral Small 3.2 share?

2 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Mistral Small 3.2 has 6.

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