Noometry

Model comparison

GLM-4.5V vs Mistral Medium

GLM-4.5V is the stronger model overall, scoring 39.8 to 36.3 on the Noometry Index.

Last verified . 15 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.8

Rank #158 Confirmed

Mistral Medium Mistral AI

36.3

Rank #218 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GLM-4.5V scores higher in 4 categories and Mistral Medium in 5 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.5V leads 37.5 to 25.0.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 50% for Mistral Medium.
  • GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium.
  • Mistral Medium accepts more context: 262K tokens versus 64K.

Side by side

GLM-4.5VMistral Medium
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index39.836.3
Released2025-08-112023-12-11
WeightsOpenOpen
Context window64K262K
Max output16K262K
Input $ / M tokens$0.60$1.50
Output $ / M tokens$1.80$7.50
Results tracked1536

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 39.5 (#155), Mistral Medium: 34.2 (#243)

BenchmarkGLM-4.5VMistral Medium
LMArena Coding13471434
FrontierCode—8%
SciCode—40.2%
WeirdML—43.7%
ALE-Bench—763.98

Agentic & Tool Use Not comparable

GLM-4.5V: —, Mistral Medium: 28.3 (#90)

BenchmarkGLM-4.5VMistral Medium
Berkeley Function Calling Leaderboard—37.7%

Reasoning GLM-4.5V leads

GLM-4.5V: 27.4 (#119), Mistral Medium: 24.0 (#167)

BenchmarkGLM-4.5VMistral Medium
Kagi LLM Benchmark59.8%50%
LMArena Hard Prompts13341426
CritPt—0%
DTBench—75.5%
LMCA—26.1%
Surface Evolver Bench—26.9%

Math GLM-4.5V leads

GLM-4.5V: 37.4 (#159), Mistral Medium: 28.1 (#245)

BenchmarkGLM-4.5VMistral Medium
LMArena Math13541408
OTIS Mock AIME 2024-2025—32.2%
ProofBench—9%
MATH Level 5—81.6%
FrontierMath (Feb 2025 set)—0.3%

Knowledge GLM-4.5V leads

GLM-4.5V: 37.5 (#156), Mistral Medium: 25.0 (#265)

BenchmarkGLM-4.5VMistral Medium
LMArena Expert13531408
GPQA Diamond—59.5%
Humanity's Last Exam—4.5%
Vectara Hallucination Rate—22.7%

Multimodal Mistral Medium leads

GLM-4.5V: 34.3 (#92), Mistral Medium: 35.3 (#88)

BenchmarkGLM-4.5VMistral Medium
LMArena Vision11541172

Multilingual Mistral Medium leads

GLM-4.5V: 44.6 (#177), Mistral Medium: 52.1 (#91)

BenchmarkGLM-4.5VMistral Medium
LMArena Non-English13031408
LMArena Chinese13371447
LMArena Russian12981411
LMArena Spanish13361433
LMArena French—1459
LMArena German—1432
LMArena Japanese—1378
LMArena Korean—1380

Instruction Following Mistral Medium leads

GLM-4.5V: 69.2 (#175), Mistral Medium: 73.7 (#116)

BenchmarkGLM-4.5VMistral Medium
LMArena Instruction Following13111398

Long Context Mistral Medium leads

GLM-4.5V: 39.6 (#171), Mistral Medium: 42.9 (#114)

BenchmarkGLM-4.5VMistral Medium
LMArena Longer Query13041406

Writing & Preference Mistral Medium leads

GLM-4.5V: 52.5 (#170), Mistral Medium: 60.0 (#103)

BenchmarkGLM-4.5VMistral Medium
LMArena Text13331424
LMArena Creative Writing12951391
LMArena Multi-Turn13321418
Short-Story Creative Writing—77.3%

Frequently asked questions

Is GLM-4.5V better than Mistral Medium?

GLM-4.5V is the stronger model overall, scoring 39.8 to 36.3 on the Noometry Index.

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

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

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

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 34.2 in the Noometry coding category.

Which has the bigger context window?

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

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

15 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Mistral Medium has 36.

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