Noometry

Model comparison

GLM-5.3-Flash vs Qwen3.5 27B

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 41.9 on the Noometry Index.

Last verified . 20 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Qwen3.5 27B Alibaba (Qwen)

41.9

Rank #127 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and Qwen3.5 27B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 27.5.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.30 / $2.40 for Qwen3.5 27B.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 262K.

Side by side

GLM-5.3-FlashQwen3.5 27B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.841.9
Released2026-08-202026-02-23
WeightsOpenOpen
Context window1M262K
Max output131K66K
Input $ / M tokens$0.15$0.30
Output $ / M tokens$0.50$2.40
Results tracked4028

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Qwen3.5 27B: 38.9 (#168)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena WebDev16091358
LMArena Coding15081427
ALE-Bench303.55349.45
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
FrontierSWE18.1%—
SciCode51.6%—
WeirdML—39.5%

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), Qwen3.5 27B: —

BenchmarkGLM-5.3-FlashQwen3.5 27B
APEX-Agents52.8%—
GDP.pdf14%—
Vending-Bench 2—201.98

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Qwen3.5 27B: 27.5 (#117)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Hard Prompts14911414
ARC-AGI-265.8%—
NYT Connections (extended)—47.9%
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
Thematic Generalization—45.5%
Mystery Game Puzzles8%—
DTBench—82.4%
LMCA—34%
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.88—

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), Qwen3.5 27B: 38.8 (#127)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Math15001429
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
MathArena Final-Answer Competitions—56.7%
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), Qwen3.5 27B: 38.0 (#150)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Expert15131428
GPQA Diamond90.2%—
Vectara Hallucination Rate—12.1%

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.8 (#27), Qwen3.5 27B: 39.4 (#59)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Vision12961241

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Qwen3.5 27B: 50.8 (#115)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Non-English14621390
LMArena Chinese15271478
LMArena French14961410
LMArena German14701393
LMArena Japanese14291345
LMArena Korean14461358
LMArena Russian14691390
LMArena Spanish14711407

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Qwen3.5 27B: 73.5 (#119)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Instruction Following14781393

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Qwen3.5 27B: 43.1 (#106)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Longer Query14821413

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Qwen3.5 27B: 59.3 (#111)

BenchmarkGLM-5.3-FlashQwen3.5 27B
LMArena Text14711409
LMArena Creative Writing14421362
LMArena Multi-Turn14671410

Frequently asked questions

Is GLM-5.3-Flash better than Qwen3.5 27B?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 41.9 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or Qwen3.5 27B?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Qwen3.5 27B lists at $0.30 and $2.40.

Is GLM-5.3-Flash or Qwen3.5 27B better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 38.9 in the Noometry coding category.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 262K.

How many benchmarks do GLM-5.3-Flash and Qwen3.5 27B share?

20 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Qwen3.5 27B has 28.

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