Model comparison

GLM-4.6V vs Magistral Medium

GLM-4.6V is the stronger model overall, scoring 40.9 to 34.8 on the Noometry Index.

Last verified . 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

40.9

Rank #133 Confirmed

Magistral Medium Mistral AI

34.8

Rank #224 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and Magistral Medium in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.6V leads 26.5 to 8.7.
  • GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $2 / $5 for Magistral Medium.

Side by side

GLM-4.6V and Magistral Medium specifications
GLM-4.6VMagistral Medium
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index40.934.8
Released2025-12-082025-03-17
WeightsOpenOpen
Context window128K128K
Max output33K16K
Input $ / M tokens$0.30$2
Output $ / M tokens$0.90$5
Results tracked1222

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.2 (#128), Magistral Medium: 38.6 (#161)

Coding benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Coding13901319
SciCode—39.2%

Reasoning GLM-4.6V leads

GLM-4.6V: 26.5 (#117), Magistral Medium: 8.7 (#342)

Reasoning benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Hard Prompts13681267
ARC-AGI-2—0%
Kagi LLM Benchmark—16.2%
ARC-AGI-1—6.1%
CritPt—0.3%

Math Not comparable

GLM-4.6V: —, Magistral Medium: 32.4 (#187)

Math benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Math—1249

Knowledge GLM-4.6V leads

GLM-4.6V: 37.4 (#148), Magistral Medium: 32.9 (#199)

Knowledge benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Expert13721222

Multimodal Not comparable

GLM-4.6V: 34.2 (#83), Magistral Medium: —

Multimodal benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Vision1164—

Multilingual GLM-4.6V leads

GLM-4.6V: 48.8 (#135), Magistral Medium: 39.8 (#219)

Multilingual benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Non-English13591232
LMArena Chinese14261225
LMArena Russian13411224
LMArena French—1268
LMArena German—1248
LMArena Japanese—1176
LMArena Korean—1125
LMArena Spanish—1269

Instruction Following GLM-4.6V leads

GLM-4.6V: 71.6 (#145), Magistral Medium: 66.2 (#207)

Instruction Following benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Instruction Following13511254

Long Context GLM-4.6V leads

GLM-4.6V: 41.3 (#138), Magistral Medium: 39.3 (#178)

Long Context benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Longer Query13581295

Writing & Preference GLM-4.6V leads

GLM-4.6V: 56.8 (#132), Magistral Medium: 46.5 (#214)

Writing & Preference benchmarks
BenchmarkGLM-4.6VMagistral Medium
LMArena Text13771255
LMArena Creative Writing13471245
LMArena Multi-Turn13591275

Frequently asked questions

Is GLM-4.6V better than Magistral Medium?

GLM-4.6V is the stronger model overall, scoring 40.9 to 34.8 on the Noometry Index.

Which is cheaper, GLM-4.6V or Magistral Medium?

GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Magistral Medium lists at $2 and $5.

Is GLM-4.6V or Magistral Medium better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 38.6 in the Noometry coding category.

Which has the bigger context window?

Both accept 128K tokens.

How many benchmarks do GLM-4.6V and Magistral Medium share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Magistral Medium has 22.

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