Noometry

Model comparison

GLM-4.7-Flash vs Qwen2.5-Max

Qwen2.5-Max is the stronger model overall, scoring 40.7 to 38.8 on the Noometry Index.

Last verified . 16 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Qwen2.5-Max Alibaba (Qwen)

40.7

Rank #146 Confirmed

Summary

  • They share 16 benchmarks with published results for both. GLM-4.7-Flash scores higher in 1 category and Qwen2.5-Max in 7 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where Qwen2.5-Max leads 55.4 to 47.4.
  • GLM-4.7-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-4.7-FlashQwen2.5-Max
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index38.840.7
Released2026-01-192025-01-25
WeightsOpenProprietary
Context window200K—
Max output131K—
Input $ / M tokens$0.06—
Output $ / M tokens$0.40—
Results tracked2127

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Qwen2.5-Max leads

GLM-4.7-Flash: 40.6 (#135), Qwen2.5-Max: 41.8 (#117)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Coding13831359
LiveBench Coding—64.4%

Reasoning Qwen2.5-Max leads

GLM-4.7-Flash: 20.9 (#229), Qwen2.5-Max: 25.6 (#147)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Hard Prompts13561360
Chess Puzzles0%—
LiveBench Reasoning—51.4%
LiveBench Data Analysis—67.9%
Epoch Capabilities Index—132.53
LiveBench—62.3%

Math Too close to call

GLM-4.7-Flash: 36.1 (#173), Qwen2.5-Max: 36.9 (#162)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Math13551369
OTIS Mock AIME 2024-202558.3%—
LiveBench Math—58.4%

Knowledge Too close to call

GLM-4.7-Flash: 35.5 (#184), Qwen2.5-Max: 35.3 (#186)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Expert13571337
GPQA Diamond60.5%—
Confabulations—21.8%
Vectara Hallucination Rate9.3%—

Multilingual Qwen2.5-Max leads

GLM-4.7-Flash: 46.5 (#158), Qwen2.5-Max: 48.1 (#146)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Non-English13301352
LMArena Chinese14031382
LMArena French13321396
LMArena German13371350
LMArena Korean12831304
LMArena Russian13321353
LMArena Spanish13501377
LMArena Japanese—1300

Instruction Following Qwen2.5-Max leads

GLM-4.7-Flash: 70.1 (#167), Qwen2.5-Max: 71.3 (#152)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Instruction Following13271335
LiveBench Instruction Following—75.3%

Long Context Too close to call

GLM-4.7-Flash: 40.9 (#148), Qwen2.5-Max: 41.4 (#142)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Longer Query13451358

Writing & Preference Qwen2.5-Max leads

GLM-4.7-Flash: 47.4 (#210), Qwen2.5-Max: 55.4 (#146)

BenchmarkGLM-4.7-FlashQwen2.5-Max
LMArena Text13511367
LMArena Creative Writing12971339
LMArena Multi-Turn13421364
Short-Story Creative Writing—72.9%
EQ-Bench Creative Writing1125—
LiveBench Language—56.3%

Frequently asked questions

Is GLM-4.7-Flash better than Qwen2.5-Max?

Qwen2.5-Max is the stronger model overall, scoring 40.7 to 38.8 on the Noometry Index.

Is GLM-4.7-Flash or Qwen2.5-Max better for coding?

Qwen2.5-Max scores higher on coding benchmarks: 41.8 versus 40.6 in the Noometry coding category.

How many benchmarks do GLM-4.7-Flash and Qwen2.5-Max share?

16 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen2.5-Max has 27.

Related comparisons

Go deeper