Noometry

Model comparison

GLM-5.3-Flash vs QwQ-32B

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 39.8 on the Noometry Index.

Last verified . 21 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

QwQ-32B Alibaba (Qwen)

39.8

Rank #159 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-5.3-Flash scores higher in 7 categories and QwQ-32B in 1 category; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 23.7.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 59.2% for QwQ-32B.

Side by side

GLM-5.3-FlashQwQ-32B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.839.8
Released2026-08-202024-11-28
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.50—
Results tracked4036

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), QwQ-32B: 35.4 (#226)

BenchmarkGLM-5.3-FlashQwQ-32B
LMArena Coding15081333
DeepSWE63.4%—
FrontierCode31.8%—
Aider Polyglot—20.9%
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
BigCodeBench Instruct—44.6%
LiveBench Coding—72.2%
BigCodeBench Complete—54.4%
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), QwQ-32B: —

BenchmarkGLM-5.3-FlashQwQ-32B
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), QwQ-32B: 23.7 (#174)

BenchmarkGLM-5.3-FlashQwQ-32B
Chess Puzzles14%5%
LMArena Hard Prompts14911325
Epoch Capabilities Index151.88137.6
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
LiveBench Reasoning—83.5%
Mystery Game Puzzles8%—
LiveBench Data Analysis—65%
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
ForecastBench—58.3
LiveBench—72%

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), QwQ-32B: 38.0 (#143)

BenchmarkGLM-5.3-FlashQwQ-32B
OTIS Mock AIME 2024-202593.9%59.2%
LMArena Math15001359
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
ProofBench21%—
LiveBench Math—77.8%

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), QwQ-32B: 37.2 (#158)

BenchmarkGLM-5.3-FlashQwQ-32B
GPQA Diamond90.2%65.3%
LMArena Expert15131324
Confabulations—15.6%

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), QwQ-32B: —

BenchmarkGLM-5.3-FlashQwQ-32B
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), QwQ-32B: 44.8 (#176)

BenchmarkGLM-5.3-FlashQwQ-32B
LMArena Non-English14621305
LMArena Chinese15271378
LMArena French14961336
LMArena German14701313
LMArena Japanese14291262
LMArena Korean14461279
LMArena Russian14691297
LMArena Spanish14711354

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), QwQ-32B: 72.6 (#137)

BenchmarkGLM-5.3-FlashQwQ-32B
LMArena Instruction Following14781297
LiveBench Instruction Following—81.8%

Long Context QwQ-32B leads

GLM-5.3-Flash: 45.4 (#39), QwQ-32B: 49.0 (#11)

BenchmarkGLM-5.3-FlashQwQ-32B
LMArena Longer Query14821308
Fiction.LiveBench—83.3%

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), QwQ-32B: 50.6 (#180)

BenchmarkGLM-5.3-FlashQwQ-32B
LMArena Text14711329
LMArena Creative Writing14421288
LMArena Multi-Turn14671314
Short-Story Creative Writing—80.2%
EQ-Bench Creative Writing—1257
LiveBench Language—51.4%

Frequently asked questions

Is GLM-5.3-Flash better than QwQ-32B?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 39.8 on the Noometry Index.

Is GLM-5.3-Flash or QwQ-32B better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 35.4 in the Noometry coding category.

How many benchmarks do GLM-5.3-Flash and QwQ-32B share?

21 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and QwQ-32B has 36.

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