Noometry

Model comparison

GLM-5.3-Flash vs Qwen2.5 Plus 1127

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 38.1 on the Noometry Index.

Last verified . 14 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

49.6

Rank #45 Confirmed

Qwen2.5 Plus 1127 Alibaba (Qwen)

38.1

Rank #179 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Qwen2.5 Plus 1127 in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 34.9.
  • GLM-5.3-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-5.3-FlashQwen2.5 Plus 1127
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index49.638.1
Released2026-08-20—
WeightsOpenProprietary
Context window1M—
Max output131K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.50—
Results tracked3614

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.7 (#26), Qwen2.5 Plus 1127: 37.9 (#171)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Coding15061314
DeepSWE63.4%—
FrontierCode31.8%—
LMArena WebDev1614—
SciCode51.6%—
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.3 (#41), Qwen2.5 Plus 1127: —

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 31.7 (#69), Qwen2.5 Plus 1127: 24.8 (#139)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Hard Prompts14901299
CritPt15.4%—
Chess Puzzles14%—
Mystery Game Puzzles8%—
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.9—

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#38), Qwen2.5 Plus 1127: 33.5 (#175)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Math14991298
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#33), Qwen2.5 Plus 1127: 34.9 (#179)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Expert15121289
GPQA Diamond90.2%—

Multimodal Not comparable

GLM-5.3-Flash: 42.6 (#25), Qwen2.5 Plus 1127: —

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Vision1304—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.2 (#24), Qwen2.5 Plus 1127: 42.1 (#196)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Non-English14621265
LMArena Chinese15291314
LMArena German14571231
LMArena Japanese14201207
LMArena Russian14721271
LMArena French1495—
LMArena Korean1443—
LMArena Spanish1471—

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.8 (#17), Qwen2.5 Plus 1127: 67.4 (#194)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Instruction Following14801275

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.3 (#41), Qwen2.5 Plus 1127: 39.2 (#180)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Longer Query14791292

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.4 (#49), Qwen2.5 Plus 1127: 49.5 (#186)

BenchmarkGLM-5.3-FlashQwen2.5 Plus 1127
LMArena Text14711299
LMArena Creative Writing14401262
LMArena Multi-Turn14711299

Frequently asked questions

Is GLM-5.3-Flash better than Qwen2.5 Plus 1127?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 38.1 on the Noometry Index.

Is GLM-5.3-Flash or Qwen2.5 Plus 1127 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 37.9 in the Noometry coding category.

How many benchmarks do GLM-5.3-Flash and Qwen2.5 Plus 1127 share?

14 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and Qwen2.5 Plus 1127 has 14.

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