Noometry

Model comparison

GLM-4.5V vs Mistral Medium 3.5

GLM-4.5V and Mistral Medium 3.5 score almost the same on the Noometry Index (39.8 vs 40.2), 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 Medium 3.5 Mistral AI

40.2

Rank #152 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GLM-4.5V scores higher in 2 categories and Mistral Medium 3.5 in 7 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.5V leads 27.4 to 17.3.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 41.4% for Mistral Medium 3.5.
  • GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
  • Mistral Medium 3.5 accepts more context: 262K tokens versus 64K.

Side by side

GLM-4.5VMistral Medium 3.5
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index39.840.2
Released2025-08-11—
WeightsOpenOpen
Context window64K262K
Max output16K210K
Input $ / M tokens$0.60$1.50
Output $ / M tokens$1.80$7.50
Results tracked1522

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), Mistral Medium 3.5: 36.0 (#213)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Coding13471461
LMArena WebDev—1264

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), Mistral Medium 3.5: 17.3 (#295)

BenchmarkGLM-4.5VMistral Medium 3.5
Kagi LLM Benchmark59.8%41.4%
LMArena Hard Prompts13341436
NYT Connections (extended)—12.9%
Epoch Capabilities Index—141.35

Math Mistral Medium 3.5 leads

GLM-4.5V: 37.4 (#159), Mistral Medium 3.5: 39.1 (#113)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Math13541431

Knowledge Mistral Medium 3.5 leads

GLM-4.5V: 37.5 (#156), Mistral Medium 3.5: 40.0 (#126)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Expert13531432

Multimodal Mistral Medium 3.5 leads

GLM-4.5V: 34.3 (#92), Mistral Medium 3.5: 38.3 (#65)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Vision11541223

Multilingual Mistral Medium 3.5 leads

GLM-4.5V: 44.6 (#177), Mistral Medium 3.5: 51.9 (#100)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Non-English13031404
LMArena Chinese13371442
LMArena Russian12981395
LMArena Spanish13361409
LMArena French—1448
LMArena German—1451
LMArena Korean—1385

Instruction Following Mistral Medium 3.5 leads

GLM-4.5V: 69.2 (#175), Mistral Medium 3.5: 74.6 (#90)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Instruction Following13111415

Long Context Mistral Medium 3.5 leads

GLM-4.5V: 39.6 (#171), Mistral Medium 3.5: 43.2 (#103)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Longer Query13041415

Writing & Preference Mistral Medium 3.5 leads

GLM-4.5V: 52.5 (#170), Mistral Medium 3.5: 58.5 (#117)

BenchmarkGLM-4.5VMistral Medium 3.5
LMArena Text13331421
LMArena Creative Writing12951374
LMArena Multi-Turn13321423
EQ-Bench 4—993

Frequently asked questions

Is GLM-4.5V better than Mistral Medium 3.5?

GLM-4.5V and Mistral Medium 3.5 score almost the same on the Noometry Index (39.8 vs 40.2), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5V or Mistral Medium 3.5?

GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is GLM-4.5V or Mistral Medium 3.5 better for coding?

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 36.0 in the Noometry coding category.

Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 64K.

How many benchmarks do GLM-4.5V and Mistral Medium 3.5 share?

15 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Mistral Medium 3.5 has 22.

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