Noometry

Model comparison

GLM-5.3-Flash vs Qwen2.5-VL 72B Instruct

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 29.9 on the Noometry Index.

Last verified . 1 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Qwen2.5-VL 72B Instruct Alibaba (Qwen)

29.9

Rank #302 Confirmed

Summary

  • They share 1 benchmark with published results for both. GLM-5.3-Flash scores higher in 3 categories and Qwen2.5-VL 72B Instruct in 0 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 20.7.
  • GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
  • GLM-5.3-Flash accepts more context: 1M tokens versus 131K.

Side by side

GLM-5.3-FlashQwen2.5-VL 72B Instruct
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index51.829.9
Released2026-08-202024-09
WeightsOpenOpen
Context window1M131K
Max output131K8K
Input $ / M tokens$0.15$2.80
Output $ / M tokens$0.50$8.40
Results tracked406

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Category by category

Coding Not comparable

GLM-5.3-Flash: 53.1 (#31), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
LMArena Coding1508—
ALE-Bench303.55—

Agentic & Tool Use GLM-5.3-Flash leads

GLM-5.3-Flash: 34.2 (#47), Qwen2.5-VL 72B Instruct: 18.6 (#144)

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
APEX-Agents52.8%—
OSWorld—5%
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Qwen2.5-VL 72B Instruct: 20.7 (#233)

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
ARC-AGI-265.8%—
Kagi LLM Benchmark—36%
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
LMArena Hard Prompts1491—
Mystery Game Puzzles8%—
Surface Evolver Bench52.5%—
Bench to the Future 30.15—
Epoch Capabilities Index151.88—

Math Not comparable

GLM-5.3-Flash: 53.3 (#47), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
FrontierMath (Tiers 1-3)55.8%—
FrontierMath Tier 417.1%—
OTIS Mock AIME 2024-202593.9%—
ProofBench21%—
LMArena Math1500—

Knowledge Not comparable

GLM-5.3-Flash: 58.4 (#36), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
GPQA Diamond90.2%—
LMArena Expert1513—

Multimodal GLM-5.3-Flash leads

GLM-5.3-Flash: 42.8 (#27), Qwen2.5-VL 72B Instruct: 33.5 (#97)

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
LMArena Vision12961107
Video-MME—73.5%
GeoBench—62%
SpatialViz-Bench—33.3%

Multilingual Not comparable

GLM-5.3-Flash: 56.0 (#25), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
LMArena Non-English1462—
LMArena Chinese1527—
LMArena French1496—
LMArena German1470—
LMArena Japanese1429—
LMArena Korean1446—
LMArena Russian1469—
LMArena Spanish1471—

Instruction Following Not comparable

GLM-5.3-Flash: 77.5 (#20), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
LMArena Instruction Following1478—

Long Context Not comparable

GLM-5.3-Flash: 45.4 (#39), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
LMArena Longer Query1482—

Writing & Preference Not comparable

GLM-5.3-Flash: 65.3 (#50), Qwen2.5-VL 72B Instruct: —

BenchmarkGLM-5.3-FlashQwen2.5-VL 72B Instruct
LMArena Text1471—
LMArena Creative Writing1442—
LMArena Multi-Turn1467—

Frequently asked questions

Is GLM-5.3-Flash better than Qwen2.5-VL 72B Instruct?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 29.9 on the Noometry Index.

Which is cheaper, GLM-5.3-Flash or Qwen2.5-VL 72B Instruct?

GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.

Which has the bigger context window?

GLM-5.3-Flash does, with 1M tokens against 131K.

How many benchmarks do GLM-5.3-Flash and Qwen2.5-VL 72B Instruct share?

1 benchmark has published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.

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