Noometry

Model comparison

GLM-4.7-Flash vs Magistral Small

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.2 on the Noometry Index.

Last verified . 3 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Magistral Small Mistral AI

30.2

Rank #296 Confirmed

Summary

  • They share 3 benchmarks with published results for both. GLM-4.7-Flash 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-Flash leads 20.9 to 6.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 30% for Magistral Small.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.50 / $1.50 for Magistral Small.
  • GLM-4.7-Flash accepts more context: 200K tokens versus 128K.

Side by side

GLM-4.7-FlashMagistral Small
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index38.830.2
Released2026-01-192025-06-10
WeightsOpenOpen
Context window200K128K
Max output131K40K
Input $ / M tokens$0.06$0.50
Output $ / M tokens$0.40$1.50
Results tracked2110

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.7-Flash: 40.6 (#135), Magistral Small: 38.4 (#176)

BenchmarkGLM-4.7-FlashMagistral Small
SciCode—35.2%
LMArena Coding1383—

Reasoning GLM-4.7-Flash leads

GLM-4.7-Flash: 20.9 (#229), Magistral Small: 6.8 (#350)

BenchmarkGLM-4.7-FlashMagistral Small
Chess Puzzles0%3%
ARC-AGI-2—0%
Kagi LLM Benchmark—6.3%
ARC-AGI-1—5%
CritPt—0.3%
LMArena Hard Prompts1356—
DTBench—61.3%
Epoch Capabilities Index—133.19

Math GLM-4.7-Flash leads

GLM-4.7-Flash: 36.1 (#173), Magistral Small: 26.2 (#261)

BenchmarkGLM-4.7-FlashMagistral Small
OTIS Mock AIME 2024-202558.3%30%
LMArena Math1355—

Knowledge GLM-4.7-Flash leads

GLM-4.7-Flash: 35.5 (#184), Magistral Small: 30.9 (#223)

BenchmarkGLM-4.7-FlashMagistral Small
GPQA Diamond60.5%56.1%
Vectara Hallucination Rate9.3%—
LMArena Expert1357—

Multilingual Not comparable

GLM-4.7-Flash: 46.5 (#158), Magistral Small: —

BenchmarkGLM-4.7-FlashMagistral Small
LMArena Non-English1330—
LMArena Chinese1403—
LMArena French1332—
LMArena German1337—
LMArena Korean1283—
LMArena Russian1332—
LMArena Spanish1350—

Instruction Following Not comparable

GLM-4.7-Flash: 70.1 (#167), Magistral Small: —

BenchmarkGLM-4.7-FlashMagistral Small
LMArena Instruction Following1327—

Long Context Not comparable

GLM-4.7-Flash: 40.9 (#148), Magistral Small: —

BenchmarkGLM-4.7-FlashMagistral Small
LMArena Longer Query1345—

Writing & Preference Not comparable

GLM-4.7-Flash: 47.4 (#210), Magistral Small: —

BenchmarkGLM-4.7-FlashMagistral Small
LMArena Text1351—
LMArena Creative Writing1297—
EQ-Bench Creative Writing1125—
LMArena Multi-Turn1342—

Frequently asked questions

Is GLM-4.7-Flash better than Magistral Small?

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.2 on the Noometry Index.

Which is cheaper, GLM-4.7-Flash or Magistral Small?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Magistral Small lists at $0.50 and $1.50.

Is GLM-4.7-Flash or Magistral Small better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 38.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7-Flash does, with 200K tokens against 128K.

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

3 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Magistral Small has 10.

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