Noometry

Model comparison

GLM-5.3-Flash vs Hunyuan T1 20250711

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 42.5 on the Noometry Index.

Last verified . 13 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Hunyuan T1 20250711 Tencent

42.5

Rank #114 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Hunyuan T1 20250711 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 38.8.
  • GLM-5.3-Flash has downloadable open weights; the other is API-only.

Side by side

GLM-5.3-FlashHunyuan T1 20250711
ProviderZ.ai (Zhipu)Tencent
Noometry Index51.842.5
Released2026-08-20—
WeightsOpenProprietary
Context window1M—
Max output131K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.50—
Results tracked4013

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Hunyuan T1 20250711: 40.9 (#129)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Coding15081390
DeepSWE63.4%—
FrontierCode31.8%—
CursorBench36.8%—
LMArena WebDev1609—
FrontierSWE18.1%—
SciCode51.6%—
ALE-Bench303.55—

Agentic & Tool Use Not comparable

GLM-5.3-Flash: 34.2 (#47), Hunyuan T1 20250711: —

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Hunyuan T1 20250711: 28.5 (#103)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Hard Prompts14911399
ARC-AGI-265.8%—
ARC-AGI-191%—
CritPt15.4%—
Chess Puzzles14%—
Mystery Game Puzzles8%—
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), Hunyuan T1 20250711: 38.7 (#130)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Math15001414
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 (#36), Hunyuan T1 20250711: 38.8 (#141)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Expert15131395
GPQA Diamond90.2%—

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), Hunyuan T1 20250711: —

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Hunyuan T1 20250711: 51.2 (#112)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Non-English14621395
LMArena Chinese15271425
LMArena Korean14461406
LMArena Russian14691385
LMArena French1496—
LMArena German1470—
LMArena Japanese1429—
LMArena Spanish1471—

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Hunyuan T1 20250711: 72.6 (#138)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Instruction Following14781374

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Hunyuan T1 20250711: 42.2 (#128)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Longer Query14821384

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Hunyuan T1 20250711: 59.5 (#109)

BenchmarkGLM-5.3-FlashHunyuan T1 20250711
LMArena Text14711401
LMArena Creative Writing14421392
LMArena Multi-Turn14671393

Frequently asked questions

Is GLM-5.3-Flash better than Hunyuan T1 20250711?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 42.5 on the Noometry Index.

Is GLM-5.3-Flash or Hunyuan T1 20250711 better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 40.9 in the Noometry coding category.

How many benchmarks do GLM-5.3-Flash and Hunyuan T1 20250711 share?

13 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Hunyuan T1 20250711 has 13.

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