Noometry

Model comparison

GLM-4.6 vs Mistral Medium 3.5

GLM-4.6 is the stronger model overall, scoring 41.4 to 40.2 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Mistral Medium 3.5 Mistral AI

40.2

Rank #152 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.6 scores higher in 7 categories and Mistral Medium 3.5 in 1 category; 4 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-4.6 leads 23.7 to 17.3.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 and 41.4% for Mistral Medium 3.5.
  • GLM-4.6 is cheaper at $0.60 / $2.20 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 205K.

Side by side

GLM-4.6Mistral Medium 3.5
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index41.440.2
Released2025-09-30—
WeightsOpenOpen
Context window205K262K
Max output131K210K
Input $ / M tokens$0.60$1.50
Output $ / M tokens$2.20$7.50
Results tracked2922

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 40.1 (#148), Mistral Medium 3.5: 36.0 (#213)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena WebDev13401264
LMArena Coding14491461
SWE-bench Verified (bash only)55.4%—
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Mistral Medium 3.5: —

BenchmarkGLM-4.6Mistral Medium 3.5
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.7 (#172), Mistral Medium 3.5: 17.3 (#295)

BenchmarkGLM-4.6Mistral Medium 3.5
Kagi LLM Benchmark47.4%41.4%
LMArena Hard Prompts14401436
NYT Connections (extended)—12.9%
CritPt1.1%—
Epoch Capabilities Index—141.35

Math Too close to call

GLM-4.6: 39.1 (#111), Mistral Medium 3.5: 39.1 (#113)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Math14321431
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge Too close to call

GLM-4.6: 40.2 (#124), Mistral Medium 3.5: 40.0 (#126)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Expert14311432
Vectara Hallucination Rate9.5%—

Multimodal Not comparable

GLM-4.6: —, Mistral Medium 3.5: 38.3 (#65)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Vision—1223

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Mistral Medium 3.5: 51.9 (#100)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Non-English14261404
LMArena Chinese14991442
LMArena French14591448
LMArena German14471451
LMArena Korean14001385
LMArena Russian14191395
LMArena Spanish14361409
LMArena Japanese1393—

Instruction Following Too close to call

GLM-4.6: 74.3 (#98), Mistral Medium 3.5: 74.6 (#90)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Instruction Following14101415

Long Context Too close to call

GLM-4.6: 43.4 (#94), Mistral Medium 3.5: 43.2 (#103)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Longer Query14221415

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Mistral Medium 3.5: 58.5 (#117)

BenchmarkGLM-4.6Mistral Medium 3.5
LMArena Text14401421
LMArena Creative Writing14111374
LMArena Multi-Turn14271423
EQ-Bench Creative Writing1411—
EQ-Bench 4—993

Frequently asked questions

Is GLM-4.6 better than Mistral Medium 3.5?

GLM-4.6 is the stronger model overall, scoring 41.4 to 40.2 on the Noometry Index.

Which is cheaper, GLM-4.6 or Mistral Medium 3.5?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is GLM-4.6 or Mistral Medium 3.5 better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 36.0 in the Noometry coding category.

Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 205K.

How many benchmarks do GLM-4.6 and Mistral Medium 3.5 share?

18 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Mistral Medium 3.5 has 22.

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