Noometry

Model comparison

GLM-4.7 vs Magistral Small

GLM-4.7 is the stronger model overall, scoring 41.7 to 29.9 on the Noometry Index.

Last verified . 6 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

Magistral Small Mistral AI

29.9

Rank #289 Confirmed

Summary

  • They share 6 benchmarks with published results for both. GLM-4.7 scores higher in 4 categories and Magistral Small in 0 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.7 leads 23.7 to 6.9.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 83.3% for GLM-4.7 and 30% for Magistral Small.
  • Magistral Small is cheaper at $0.50 / $1.50 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
  • GLM-4.7 accepts more context: 205K tokens versus 128K.

Side by side

GLM-4.7Magistral Small
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index41.729.9
Released2025-12-222025-06-10
WeightsOpenOpen
Context window205K128K
Max output131K40K
Input $ / M tokens$0.60$0.50
Output $ / M tokens$2.20$1.50
Results tracked3610

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 43.6 (#74), Magistral Small: 37.8 (#172)

BenchmarkGLM-4.7Magistral Small
SciCode45.1%35.2%
LMArena WebDev1435—
LMArena Coding1454—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

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

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

Reasoning GLM-4.7 leads

GLM-4.7: 23.7 (#161), Magistral Small: 6.9 (#345)

BenchmarkGLM-4.7Magistral Small
CritPt1.7%0.3%
Chess Puzzles6%3%
Epoch Capabilities Index143.53133.19
ARC-AGI-2—0%
SimpleBench47.7%—
Kagi LLM Benchmark—6.3%
ARC-AGI-1—5%
LMArena Hard Prompts1443—
DTBench—61.3%

Math GLM-4.7 leads

GLM-4.7: 37.7 (#92), Magistral Small: 24.9 (#253)

BenchmarkGLM-4.7Magistral Small
OTIS Mock AIME 2024-202583.3%30%
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), Magistral Small: 30.9 (#215)

BenchmarkGLM-4.7Magistral Small
GPQA Diamond83.3%56.1%
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—
LMArena Expert1424—

Multilingual Not comparable

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

BenchmarkGLM-4.7Magistral Small
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), Magistral Small: —

BenchmarkGLM-4.7Magistral Small
LMArena Instruction Following1411—

Long Context Not comparable

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

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

Writing & Preference Not comparable

GLM-4.7: 61.1 (#89), Magistral Small: —

BenchmarkGLM-4.7Magistral Small
LMArena Text1436—
LMArena Creative Writing1401—
EQ-Bench Creative Writing1413—
LMArena Multi-Turn1446—

Frequently asked questions

Is GLM-4.7 better than Magistral Small?

GLM-4.7 is the stronger model overall, scoring 41.7 to 29.9 on the Noometry Index.

Which is cheaper, GLM-4.7 or Magistral Small?

Magistral Small is cheaper. It lists at $0.50 per million input tokens and $1.50 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

Is GLM-4.7 or Magistral Small better for coding?

GLM-4.7 scores higher on coding benchmarks: 43.6 versus 37.8 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 128K.

How many benchmarks do GLM-4.7 and Magistral Small share?

6 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Magistral Small has 10.

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