Noometry

Model comparison

GLM-4.5V vs Mistral Large 3

GLM-4.5V and Mistral Large 3 score almost the same on the Noometry Index (39.8 vs 39.1), so choose on price, context window or the category you care about most.

Last verified . 15 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

Mistral Large 3 Mistral AI

39.1

Rank #176 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GLM-4.5V scores higher in 3 categories and Mistral Large 3 in 6 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.5V leads 27.4 to 15.2.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 50.9% for Mistral Large 3.
  • Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
  • Mistral Large 3 accepts more context: 262K tokens versus 64K.

Side by side

GLM-4.5VMistral Large 3
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index39.839.1
Released2025-08-112025-12-02
WeightsOpenOpen
Context window64K262K
Max output16K8K
Input $ / M tokens$0.60$0.25
Output $ / M tokens$1.80$0.75
Results tracked1524

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), Mistral Large 3: 34.4 (#237)

BenchmarkGLM-4.5VMistral Large 3
LMArena Coding13471448
LMArena WebDev—1230

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), Mistral Large 3: 15.2 (#319)

BenchmarkGLM-4.5VMistral Large 3
Kagi LLM Benchmark59.8%50.9%
LMArena Hard Prompts13341429
NYT Connections (extended)—7.5%
Thematic Generalization—23%

Math Mistral Large 3 leads

GLM-4.5V: 37.4 (#159), Mistral Large 3: 38.7 (#129)

BenchmarkGLM-4.5VMistral Large 3
LMArena Math13541414

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), Mistral Large 3: 36.0 (#177)

BenchmarkGLM-4.5VMistral Large 3
LMArena Expert13531421
Vectara Hallucination Rate—14.5%

Multimodal Mistral Large 3 leads

GLM-4.5V: 34.3 (#92), Mistral Large 3: 38.2 (#66)

BenchmarkGLM-4.5VMistral Large 3
LMArena Vision11541221

Multilingual Mistral Large 3 leads

GLM-4.5V: 44.6 (#177), Mistral Large 3: 52.5 (#84)

BenchmarkGLM-4.5VMistral Large 3
LMArena Non-English13031413
LMArena Chinese13371447
LMArena Russian12981411
LMArena Spanish13361440
LMArena French—1455
LMArena German—1437
LMArena Japanese—1394
LMArena Korean—1384

Instruction Following Mistral Large 3 leads

GLM-4.5V: 69.2 (#175), Mistral Large 3: 74.0 (#108)

BenchmarkGLM-4.5VMistral Large 3
LMArena Instruction Following13111403

Long Context Mistral Large 3 leads

GLM-4.5V: 39.6 (#171), Mistral Large 3: 43.1 (#105)

BenchmarkGLM-4.5VMistral Large 3
LMArena Longer Query13041413

Writing & Preference Mistral Large 3 leads

GLM-4.5V: 52.5 (#170), Mistral Large 3: 60.0 (#101)

BenchmarkGLM-4.5VMistral Large 3
LMArena Text13331428
LMArena Creative Writing12951386
LMArena Multi-Turn13321429
EQ-Bench Creative Writing—1412

Frequently asked questions

Is GLM-4.5V better than Mistral Large 3?

GLM-4.5V and Mistral Large 3 score almost the same on the Noometry Index (39.8 vs 39.1), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5V or Mistral Large 3?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or Mistral Large 3 better for coding?

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 34.4 in the Noometry coding category.

Which has the bigger context window?

Mistral Large 3 does, with 262K tokens against 64K.

How many benchmarks do GLM-4.5V and Mistral Large 3 share?

15 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Mistral Large 3 has 24.

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