Noometry

Model comparison

GLM-4.7 vs Mistral Small 3.2

GLM-4.7 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-4.7's lead doesn't matter for your workload.

Last verified . 5 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Mistral Small 3.2 Mistral AI

31.2

Rank #280 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 26.7.
  • 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 Index42.031.2
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: 44.0 (#79), 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: 26.5 (#103), 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: 24.3 (#164), Mistral Small 3.2: 18.1 (#287)

BenchmarkGLM-4.7Mistral Small 3.2
Chess Puzzles6%1%
Epoch Capabilities Index143.51131.74
SimpleBench47.7%—
Kagi LLM Benchmark—40.4%
CritPt1.7%—
LMArena Hard Prompts1443—

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), Mistral Small 3.2: 26.3 (#260)

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 (#80), Mistral Small 3.2: 26.7 (#256)

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: 52.8 (#79), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
LMArena Non-English1417—
LMArena Chinese1495—
LMArena French1432—
LMArena German1424—
LMArena Japanese1439—
LMArena Korean1399—
LMArena Russian1423—
LMArena Spanish1434—

Instruction Following Not comparable

GLM-4.7: 74.4 (#95), Mistral Small 3.2: —

BenchmarkGLM-4.7Mistral Small 3.2
LMArena Instruction Following1411—

Long Context Not comparable

GLM-4.7: 42.8 (#116), 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: 60.9 (#93), Mistral Small 3.2: 45.0 (#224)

BenchmarkGLM-4.7Mistral Small 3.2
EQ-Bench Creative Writing14131255
LMArena Text1435—
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 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-4.7'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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