Noometry

Model comparison

GLM-5.3-Flash vs Qwen3.8 27B

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 46.0 on the Noometry Index.

Last verified . 27 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Qwen3.8 27B Alibaba (Qwen)

46.0

Rank #68 Confirmed

Summary

  • They share 27 benchmarks with published results for both. GLM-5.3-Flash scores higher in 9 categories and Qwen3.8 27B in 1 category; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-5.3-Flash leads 58.4 to 41.6.
  • The biggest single-benchmark swing is ARC-AGI-2: 65.8% for GLM-5.3-Flash and 42.4% for Qwen3.8 27B.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $0.99 / $1.49 for Qwen3.8 27B.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 262K.

Side by side

GLM-5.3-FlashQwen3.8 27B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.846.0
Released2026-08-202026-08-14
WeightsOpenOpen
Context window1M262K
Max output131K33K
Input $ / M tokens$0.15$0.99
Output $ / M tokens$0.50$1.49
Results tracked4031

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Qwen3.8 27B: 50.5 (#44)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena WebDev16091593
SciCode51.6%46.6%
LMArena Coding15081482
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
FrontierSWE18.1%—
ALE-Bench303.55—

Agentic & Tool Use GLM-5.3-Flash leads

GLM-5.3-Flash: 34.2 (#47), Qwen3.8 27B: 32.9 (#57)

BenchmarkGLM-5.3-FlashQwen3.8 27B
APEX-Agents52.8%47.5%
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Qwen3.8 27B: 41.0 (#54)

BenchmarkGLM-5.3-FlashQwen3.8 27B
ARC-AGI-265.8%42.4%
ARC-AGI-191%87.5%
CritPt15.4%5.4%
LMArena Hard Prompts14911460
Surface Evolver Bench52.5%45%
Epoch Capabilities Index151.88149.38
NYT Connections (extended)—54.5%
Chess Puzzles14%—
Mystery Game Puzzles8%—
DTBench—88%
LMCA—41.4%
Bench to the Future 30.15—

Math GLM-5.3-Flash leads

GLM-5.3-Flash: 53.3 (#47), Qwen3.8 27B: 37.1 (#161)

BenchmarkGLM-5.3-FlashQwen3.8 27B
ProofBench21%16%
LMArena Math15001456
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—

Knowledge GLM-5.3-Flash leads

GLM-5.3-Flash: 58.4 (#36), Qwen3.8 27B: 41.6 (#109)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena Expert15131482
GPQA Diamond90.2%—

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.8 (#27), Qwen3.8 27B: 41.3 (#37)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena Vision12961271

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Qwen3.8 27B: 53.7 (#60)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena Non-English14621430
LMArena Chinese15271504
LMArena French14961465
LMArena German14701438
LMArena Japanese14291384
LMArena Korean14461393
LMArena Russian14691415
LMArena Spanish14711448

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Qwen3.8 27B: 75.8 (#53)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena Instruction Following14781439

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Qwen3.8 27B: 44.3 (#70)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena Longer Query14821450

Writing & Preference Too close to call

GLM-5.3-Flash: 65.3 (#50), Qwen3.8 27B: 65.8 (#43)

BenchmarkGLM-5.3-FlashQwen3.8 27B
LMArena Text14711441
LMArena Creative Writing14421384
LMArena Multi-Turn14671441
EQ-Bench Creative Writing—1671

Frequently asked questions

Is GLM-5.3-Flash better than Qwen3.8 27B?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 46.0 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or Qwen3.8 27B?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Qwen3.8 27B lists at $0.99 and $1.49.

Is GLM-5.3-Flash or Qwen3.8 27B better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 50.5 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 Qwen3.8 27B share?

27 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Qwen3.8 27B has 31.

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