Noometry

Model comparison

GLM-4.7-Flash vs Mistral Small 3.1

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 31.7 on the Noometry Index.

Last verified . 20 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Mistral Small 3.1 Mistral AI

31.7

Rank #269 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-4.7-Flash scores higher in 8 categories and Mistral Small 3.1 in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.7-Flash leads 36.1 to 14.7.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 3.9% for Mistral Small 3.1.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.35 / $0.56 for Mistral Small 3.1.
  • GLM-4.7-Flash accepts more context: 200K tokens versus 128K.

Side by side

GLM-4.7-FlashMistral Small 3.1
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index38.831.7
Released2026-01-192025-03-17
WeightsOpenOpen
Context window200K128K
Max output131K102K
Input $ / M tokens$0.06$0.35
Output $ / M tokens$0.40$0.56
Results tracked2128

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.7-Flash: 40.6 (#135), Mistral Small 3.1: 38.3 (#179)

BenchmarkGLM-4.7-FlashMistral Small 3.1
LMArena Coding13831309

Reasoning GLM-4.7-Flash leads

GLM-4.7-Flash: 20.9 (#229), Mistral Small 3.1: 19.7 (#254)

BenchmarkGLM-4.7-FlashMistral Small 3.1
Chess Puzzles0%1%
LMArena Hard Prompts13561278
Epoch Capabilities Index—127.48

Math GLM-4.7-Flash leads

GLM-4.7-Flash: 36.1 (#173), Mistral Small 3.1: 14.7 (#301)

BenchmarkGLM-4.7-FlashMistral Small 3.1
OTIS Mock AIME 2024-202558.3%3.9%
LMArena Math13551262
Omni-MATH—24.8%

Knowledge GLM-4.7-Flash leads

GLM-4.7-Flash: 35.5 (#184), Mistral Small 3.1: 22.6 (#271)

BenchmarkGLM-4.7-FlashMistral Small 3.1
GPQA Diamond60.5%41.9%
LMArena Expert13571257
MMLU-Pro—61%
Vectara Hallucination Rate9.3%—
GPQA (HELM)—39.2%

Multimodal Not comparable

GLM-4.7-Flash: —, Mistral Small 3.1: 33.2 (#99)

BenchmarkGLM-4.7-FlashMistral Small 3.1
LMArena Vision—1136

Multilingual GLM-4.7-Flash leads

GLM-4.7-Flash: 46.5 (#158), Mistral Small 3.1: 41.2 (#209)

BenchmarkGLM-4.7-FlashMistral Small 3.1
LMArena Non-English13301255
LMArena Chinese14031253
LMArena French13321273
LMArena German13371266
LMArena Korean12831206
LMArena Russian13321263
LMArena Spanish13501283
LMArena Japanese—1208

Instruction Following GLM-4.7-Flash leads

GLM-4.7-Flash: 70.1 (#167), Mistral Small 3.1: 63.6 (#230)

BenchmarkGLM-4.7-FlashMistral Small 3.1
LMArena Instruction Following13271264
IFEval—75%

Long Context GLM-4.7-Flash leads

GLM-4.7-Flash: 40.9 (#148), Mistral Small 3.1: 39.5 (#178)

BenchmarkGLM-4.7-FlashMistral Small 3.1
LMArena Longer Query13451299

Writing & Preference GLM-4.7-Flash leads

GLM-4.7-Flash: 47.4 (#210), Mistral Small 3.1: 37.0 (#259)

BenchmarkGLM-4.7-FlashMistral Small 3.1
LMArena Text13511277
LMArena Creative Writing12971253
EQ-Bench Creative Writing1125761
LMArena Multi-Turn13421270
WildBench—78.8%

Frequently asked questions

Is GLM-4.7-Flash better than Mistral Small 3.1?

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 31.7 on the Noometry Index.

Which is cheaper, GLM-4.7-Flash or Mistral Small 3.1?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Mistral Small 3.1 lists at $0.35 and $0.56.

Is GLM-4.7-Flash or Mistral Small 3.1 better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 38.3 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 Mistral Small 3.1 share?

20 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Mistral Small 3.1 has 28.

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