Noometry

Model comparison

GLM-4.5V vs Mistral Small 3.1

GLM-4.5V is the stronger model overall, scoring 39.8 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.2× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Last verified . 14 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

Mistral Small 3.1 Mistral AI

31.7

Rank #269 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 9 categories and Mistral Small 3.1 in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.5V leads 37.4 to 14.7.
  • Mistral Small 3.1 is cheaper at $0.35 / $0.56 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • Mistral Small 3.1 accepts more context: 128K tokens versus 64K.

Side by side

GLM-4.5VMistral Small 3.1
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index39.831.7
Released2025-08-112025-03-17
WeightsOpenOpen
Context window64K128K
Max output16K102K
Input $ / M tokens$0.60$0.35
Output $ / M tokens$1.80$0.56
Results tracked1528

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), Mistral Small 3.1: 38.3 (#179)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Coding13471309

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), Mistral Small 3.1: 19.7 (#254)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Hard Prompts13341278
Kagi LLM Benchmark59.8%—
Chess Puzzles—1%
Epoch Capabilities Index—127.48

Math GLM-4.5V leads

GLM-4.5V: 37.4 (#159), Mistral Small 3.1: 14.7 (#301)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Math13541262
OTIS Mock AIME 2024-2025—3.9%
Omni-MATH—24.8%

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), Mistral Small 3.1: 22.6 (#271)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Expert13531257
GPQA Diamond—41.9%
MMLU-Pro—61%
GPQA (HELM)—39.2%

Multimodal GLM-4.5V leads

GLM-4.5V: 34.3 (#92), Mistral Small 3.1: 33.2 (#99)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Vision11541136

Multilingual GLM-4.5V leads

GLM-4.5V: 44.6 (#177), Mistral Small 3.1: 41.2 (#209)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Non-English13031255
LMArena Chinese13371253
LMArena Russian12981263
LMArena Spanish13361283
LMArena French—1273
LMArena German—1266
LMArena Japanese—1208
LMArena Korean—1206

Instruction Following GLM-4.5V leads

GLM-4.5V: 69.2 (#175), Mistral Small 3.1: 63.6 (#230)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Instruction Following13111264
IFEval—75%

Long Context Too close to call

GLM-4.5V: 39.6 (#171), Mistral Small 3.1: 39.5 (#178)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Longer Query13041299

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.5 (#170), Mistral Small 3.1: 37.0 (#259)

BenchmarkGLM-4.5VMistral Small 3.1
LMArena Text13331277
LMArena Creative Writing12951253
LMArena Multi-Turn13321270
EQ-Bench Creative Writing—761
WildBench—78.8%

Frequently asked questions

Is GLM-4.5V better than Mistral Small 3.1?

GLM-4.5V is the stronger model overall, scoring 39.8 to 31.7 on the Noometry Index. Mistral Small 3.1 costs 2.2× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5V or Mistral Small 3.1?

Mistral Small 3.1 is cheaper. It lists at $0.35 per million input tokens and $0.56 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or Mistral Small 3.1 better for coding?

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 38.3 in the Noometry coding category.

Which has the bigger context window?

Mistral Small 3.1 does, with 128K tokens against 64K.

How many benchmarks do GLM-4.5V and Mistral Small 3.1 share?

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Mistral Small 3.1 has 28.

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