Noometry

Model comparison

GLM-4.7 vs Mistral Small 3.2

GLM-4.7 is the stronger model overall, scoring 41.7 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 7.5× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

Last verified . 5 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

Mistral Small 3.2 Mistral AI

30.8

Rank #271 Confirmed

Summary

  • They share 5 benchmarks with published results for both. GLM-4.7 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 knowledge, where GLM-4.7 leads 47.0 to 26.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 83.3% for GLM-4.7 and 30.3% 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-4.7.
  • Mistral Small 3.2 accepts more context: 256K tokens versus 205K.

Side by side

GLM-4.7Mistral Small 3.2
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index41.730.8
Released2025-12-222025-06-20
WeightsOpenOpen
Context window205K256K
Max output131K16K
Input $ / M tokens$0.60$0.0938
Output $ / M tokens$2.20$0.25
Results tracked366

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Category by category

Coding Not comparable

GLM-4.7: 43.6 (#74), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
LMArena WebDev1435—
SciCode45.1%—
LMArena Coding1454—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.4 (#96), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 23.7 (#161), Mistral Small 3.2: 17.5 (#282)

BenchmarkGLM-4.7Mistral Small 3.2
Chess Puzzles6%1%
Epoch Capabilities Index143.53131.73
SimpleBench47.7%—
Kagi LLM Benchmark—40.4%
CritPt1.7%—
LMArena Hard Prompts1443—

Math GLM-4.7 leads

GLM-4.7: 37.7 (#92), Mistral Small 3.2: 24.9 (#251)

BenchmarkGLM-4.7Mistral Small 3.2
OTIS Mock AIME 2024-202583.3%30.3%
ProofBench6%—
LMArena Math1423—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#74), Mistral Small 3.2: 26.8 (#249)

BenchmarkGLM-4.7Mistral Small 3.2
GPQA Diamond83.3%49.1%
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—
LMArena Expert1424—

Multilingual Not comparable

GLM-4.7: 53.0 (#75), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
LMArena Non-English1417—
LMArena Chinese1495—
LMArena French1432—
LMArena German1426—
LMArena Japanese1439—
LMArena Korean1401—
LMArena Russian1423—
LMArena Spanish1433—

Instruction Following Not comparable

GLM-4.7: 74.6 (#90), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
LMArena Instruction Following1411—

Long Context Not comparable

GLM-4.7: 42.8 (#111), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
CL-bench15.9%—
CL-bench Life10.9%—
LMArena Longer Query1432—

Writing & Preference GLM-4.7 leads

GLM-4.7: 61.1 (#89), Mistral Small 3.2: 45.1 (#219)

BenchmarkGLM-4.7Mistral Small 3.2
EQ-Bench Creative Writing14131255
LMArena Text1436—
LMArena Creative Writing1401—
LMArena Multi-Turn1446—

Frequently asked questions

Is GLM-4.7 better than Mistral Small 3.2?

GLM-4.7 is the stronger model overall, scoring 41.7 to 30.8 on the Noometry Index. Mistral Small 3.2 costs 7.5× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

Which is cheaper, GLM-4.7 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-4.7 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-4.7 and Mistral Small 3.2 share?

5 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Mistral Small 3.2 has 6.

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