Model comparison

GLM-5 vs Qwen2.5-Max

GLM-5 is the stronger model overall, scoring 46.1 to 40.7 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Qwen2.5-Max Alibaba (Qwen)

40.7

Rank #146 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-5 scores higher in 8 categories and Qwen2.5-Max in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5 leads 52.3 to 35.3.
  • GLM-5 has downloadable open weights; the other is API-only.

Side by side

GLM-5 and Qwen2.5-Max specifications
GLM-5Qwen2.5-Max
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index46.140.7
Released2026-02-112025-01-25
WeightsOpenProprietary
Context window205K—
Max output131K—
Input $ / M tokens$1—
Output $ / M tokens$3.20—
Results tracked4527

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Category by category

Coding GLM-5 leads

GLM-5: 49.0 (#52), Qwen2.5-Max: 41.8 (#117)

Coding benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Coding14611359
SWE-bench Verified72.1%—
SWE-bench Verified (bash only)72.8%—
LMArena WebDev1434—
SWE-bench Multilingual69.7%—
WeirdML48.2%—
LiveBench Coding—64.4%
ALE-Bench765.62—

Agentic & Tool Use Not comparable

GLM-5: 31.1 (#71), Qwen2.5-Max: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5Qwen2.5-Max
Terminal-Bench52.4%—
τ²-bench Airline82.5%—
τ²-bench Banking9.8%—
τ²-bench Retail73.7%—
τ²-bench Telecom86.8%—
Vending-Bench 24,432—

Reasoning GLM-5 leads

GLM-5: 27.6 (#116), Qwen2.5-Max: 25.6 (#147)

Reasoning benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Hard Prompts14521360
Epoch Capabilities Index145.83132.53
ARC-AGI-24.9%—
SimpleBench53.2%—
Kagi LLM Benchmark75%—
NYT Connections (extended)74.8%—
ARC-AGI-144.7%—
Chess Puzzles10%—
LiveBench Reasoning—51.4%
LiveBench Data Analysis—67.9%
ForecastBench61—
LiveBench—62.3%

Math GLM-5 leads

GLM-5: 46.4 (#71), Qwen2.5-Max: 36.9 (#162)

Knowledge GLM-5 leads

GLM-5: 52.3 (#64), Qwen2.5-Max: 35.3 (#186)

Knowledge benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Expert14541337
GPQA Diamond87.8%—
Confabulations—21.8%
Vectara Hallucination Rate10.1%—

Multilingual GLM-5 leads

GLM-5: 53.7 (#58), Qwen2.5-Max: 48.1 (#146)

Multilingual benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Non-English14301352
LMArena Chinese15111382
LMArena French14551396
LMArena German14451350
LMArena Japanese14161300
LMArena Korean14231304
LMArena Russian14361353
LMArena Spanish14541377

Instruction Following GLM-5 leads

GLM-5: 75.2 (#67), Qwen2.5-Max: 71.3 (#152)

Instruction Following benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Instruction Following14281335
LiveBench Instruction Following—75.3%

Long Context GLM-5 leads

GLM-5: 44.7 (#60), Qwen2.5-Max: 41.4 (#142)

Long Context benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Longer Query14461358
CL-bench18.7%—

Writing & Preference GLM-5 leads

GLM-5: 66.0 (#38), Qwen2.5-Max: 55.4 (#146)

Writing & Preference benchmarks
BenchmarkGLM-5Qwen2.5-Max
LMArena Text14461367
LMArena Creative Writing14391339
LMArena Multi-Turn14561364
Short-Story Creative Writing—72.9%
EQ-Bench Creative Writing1601—
LiveBench Language—56.3%

Frequently asked questions

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

GLM-5 is the stronger model overall, scoring 46.1 to 40.7 on the Noometry Index.

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

GLM-5 scores higher on coding benchmarks: 49.0 versus 41.8 in the Noometry coding category.

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

18 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen2.5-Max has 27.

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