Noometry

Model comparison

GLM-4.6 vs Magistral Medium

GLM-4.6 is the stronger model overall, scoring 41.4 to 35.2 on the Noometry Index.

Last verified . 20 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Magistral Medium Mistral AI

35.2

Rank #227 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-4.6 scores higher in 8 categories and Magistral Medium in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.6 leads 23.7 to 8.6.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 and 16.2% for Magistral Medium.
  • GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2 / $5 for Magistral Medium.
  • Magistral Medium accepts more context: 262K tokens versus 205K.

Side by side

GLM-4.6Magistral Medium
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index41.435.2
Released2025-09-302025-03-17
WeightsOpenOpen
Context window205K262K
Max output131K16K
Input $ / M tokens$0.60$2
Output $ / M tokens$2.20$5
Results tracked2922

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Category by category

Coding Too close to call

GLM-4.6: 40.1 (#148), Magistral Medium: 39.1 (#161)

BenchmarkGLM-4.6Magistral Medium
SciCode38.4%39.2%
LMArena Coding14491319
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1340—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Magistral Medium: —

BenchmarkGLM-4.6Magistral Medium
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.7 (#172), Magistral Medium: 8.6 (#348)

BenchmarkGLM-4.6Magistral Medium
Kagi LLM Benchmark47.4%16.2%
CritPt1.1%0.3%
LMArena Hard Prompts14401267
ARC-AGI-2—0%
ARC-AGI-1—6.1%

Math GLM-4.6 leads

GLM-4.6: 39.1 (#111), Magistral Medium: 35.1 (#189)

BenchmarkGLM-4.6Magistral Medium
LMArena Math14321250
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 40.2 (#124), Magistral Medium: 33.5 (#202)

BenchmarkGLM-4.6Magistral Medium
LMArena Expert14311223
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Magistral Medium: 39.6 (#224)

BenchmarkGLM-4.6Magistral Medium
LMArena Non-English14261232
LMArena Chinese14991227
LMArena French14591267
LMArena German14471248
LMArena Japanese13931175
LMArena Korean14001125
LMArena Russian14191224
LMArena Spanish14361271

Instruction Following GLM-4.6 leads

GLM-4.6: 74.3 (#98), Magistral Medium: 66.0 (#211)

BenchmarkGLM-4.6Magistral Medium
LMArena Instruction Following14101254

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#94), Magistral Medium: 39.3 (#183)

BenchmarkGLM-4.6Magistral Medium
LMArena Longer Query14221295

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Magistral Medium: 46.3 (#219)

BenchmarkGLM-4.6Magistral Medium
LMArena Text14401255
LMArena Creative Writing14111245
LMArena Multi-Turn14271275
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than Magistral Medium?

GLM-4.6 is the stronger model overall, scoring 41.4 to 35.2 on the Noometry Index.

Which is cheaper, GLM-4.6 or Magistral Medium?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Magistral Medium lists at $2 and $5.

Is GLM-4.6 or Magistral Medium better for coding?

They score almost the same on coding (40.1 vs 39.1); test both on your own repository before choosing.

Which has the bigger context window?

Magistral Medium does, with 262K tokens against 205K.

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

20 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Magistral Medium has 22.

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