Noometry

Model comparison

GLM-4.6 vs Qwen Max

GLM-4.6 is the stronger model overall, scoring 41.4 to 34.7 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Qwen Max Alibaba (Qwen)

34.7

Rank #230 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.6 scores higher in 7 categories and Qwen Max in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.6 leads 39.1 to 22.3.
  • GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.60 / $6.40 for Qwen Max.
  • GLM-4.6 accepts more context: 205K tokens versus 33K.
  • GLM-4.6 has downloadable open weights; the other is API-only.

Side by side

GLM-4.6Qwen Max
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index41.434.7
Released2025-09-302024-04-03
WeightsOpenProprietary
Context window205K33K
Max output131K8K
Input $ / M tokens$0.60$1.60
Output $ / M tokens$2.20$6.40
Results tracked2923

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 40.1 (#148), Qwen Max: 30.7 (#292)

BenchmarkGLM-4.6Qwen Max
LMArena Coding14491288
SWE-bench Verified (bash only)55.4%—
Aider Polyglot—21.8%
LMArena WebDev1340—
SciCode38.4%—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Qwen Max: —

BenchmarkGLM-4.6Qwen Max
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning Qwen Max leads

GLM-4.6: 23.7 (#172), Qwen Max: 25.1 (#151)

BenchmarkGLM-4.6Qwen Max
LMArena Hard Prompts14401269
Kagi LLM Benchmark47.4%—
CritPt1.1%—

Math GLM-4.6 leads

GLM-4.6: 39.1 (#111), Qwen Max: 22.3 (#276)

BenchmarkGLM-4.6Qwen Max
LMArena Math14321275
FrontierMath (Feb 2025 set)3.8%1%
OTIS Mock AIME 2024-2025—16.1%
MATH Level 5—67.2%
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 40.2 (#124), Qwen Max: 30.3 (#228)

BenchmarkGLM-4.6Qwen Max
LMArena Expert14311248
GPQA Diamond—56.1%
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Qwen Max: 41.8 (#202)

BenchmarkGLM-4.6Qwen Max
LMArena Non-English14261263
LMArena Chinese14991254
LMArena French14591330
LMArena German14471254
LMArena Japanese13931205
LMArena Korean14001142
LMArena Russian14191274
LMArena Spanish14361290

Instruction Following GLM-4.6 leads

GLM-4.6: 74.3 (#98), Qwen Max: 66.5 (#208)

BenchmarkGLM-4.6Qwen Max
LMArena Instruction Following14101262

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#94), Qwen Max: 39.4 (#180)

BenchmarkGLM-4.6Qwen Max
LMArena Longer Query14221288
Fiction.LiveBench—66.7%

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Qwen Max: 47.8 (#205)

BenchmarkGLM-4.6Qwen Max
LMArena Text14401282
LMArena Creative Writing14111248
LMArena Multi-Turn14271277
EQ-Bench Creative Writing1411—

Frequently asked questions

Is GLM-4.6 better than Qwen Max?

GLM-4.6 is the stronger model overall, scoring 41.4 to 34.7 on the Noometry Index.

Which is cheaper, GLM-4.6 or Qwen Max?

GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Qwen Max lists at $1.60 and $6.40.

Is GLM-4.6 or Qwen Max better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 30.7 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 33K.

How many benchmarks do GLM-4.6 and Qwen Max share?

18 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Qwen Max has 23.

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