Noometry

Model comparison

GLM-4.6 vs Qwen2.5-Max

GLM-4.6 and Qwen2.5-Max score almost the same on the Noometry Index (41.4 vs 40.7), so choose on price, context window or the category you care about most.

Last verified . 17 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

41.4

Rank #135 Confirmed

Qwen2.5-Max Alibaba (Qwen)

40.7

Rank #146 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-4.6 scores higher in 6 categories and Qwen2.5-Max in 2 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 55.4.
  • GLM-4.6 has downloadable open weights; the other is API-only.

Side by side

GLM-4.6Qwen2.5-Max
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index41.440.7
Released2025-09-302025-01-25
WeightsOpenProprietary
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked2927

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Category by category

Coding Qwen2.5-Max leads

GLM-4.6: 40.1 (#148), Qwen2.5-Max: 41.8 (#117)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Coding14491359
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1340—
SciCode38.4%—
LiveBench Coding—64.4%
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.3 (#66), Qwen2.5-Max: —

BenchmarkGLM-4.6Qwen2.5-Max
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning Qwen2.5-Max leads

GLM-4.6: 23.7 (#172), Qwen2.5-Max: 25.6 (#147)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Hard Prompts14401360
Kagi LLM Benchmark47.4%—
CritPt1.1%—
LiveBench Reasoning—51.4%
LiveBench Data Analysis—67.9%
Epoch Capabilities Index—132.53
LiveBench—62.3%

Math GLM-4.6 leads

GLM-4.6: 39.1 (#111), Qwen2.5-Max: 36.9 (#162)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Math14321369
LiveBench Math—58.4%
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge GLM-4.6 leads

GLM-4.6: 40.2 (#124), Qwen2.5-Max: 35.3 (#186)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Expert14311337
Confabulations—21.8%
Vectara Hallucination Rate9.5%—

Multilingual GLM-4.6 leads

GLM-4.6: 53.5 (#66), Qwen2.5-Max: 48.1 (#146)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Non-English14261352
LMArena Chinese14991382
LMArena French14591396
LMArena German14471350
LMArena Japanese13931300
LMArena Korean14001304
LMArena Russian14191353
LMArena Spanish14361377

Instruction Following GLM-4.6 leads

GLM-4.6: 74.3 (#98), Qwen2.5-Max: 71.3 (#152)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Instruction Following14101335
LiveBench Instruction Following—75.3%

Long Context GLM-4.6 leads

GLM-4.6: 43.4 (#94), Qwen2.5-Max: 41.4 (#142)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Longer Query14221358

Writing & Preference GLM-4.6 leads

GLM-4.6: 61.1 (#90), Qwen2.5-Max: 55.4 (#146)

BenchmarkGLM-4.6Qwen2.5-Max
LMArena Text14401367
LMArena Creative Writing14111339
LMArena Multi-Turn14271364
Short-Story Creative Writing—72.9%
EQ-Bench Creative Writing1411—
LiveBench Language—56.3%

Frequently asked questions

Is GLM-4.6 better than Qwen2.5-Max?

GLM-4.6 and Qwen2.5-Max score almost the same on the Noometry Index (41.4 vs 40.7), so choose on price, context window or the category you care about most.

Is GLM-4.6 or Qwen2.5-Max better for coding?

Qwen2.5-Max scores higher on coding benchmarks: 41.8 versus 40.1 in the Noometry coding category.

How many benchmarks do GLM-4.6 and Qwen2.5-Max share?

17 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Qwen2.5-Max has 27.

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