Noometry

Model comparison

GLM-5.3-Flash vs Longcat Flash Chat

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 42.1 on the Noometry Index.

Last verified . 17 shared benchmarks.

GLM-5.3-Flash Z.ai (Zhipu)

51.8

Rank #41 Confirmed

Longcat Flash Chat Meituan

42.1

Rank #120 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-5.3-Flash scores higher in 8 categories and Longcat Flash Chat in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 19.0.

Side by side

GLM-5.3-FlashLongcat Flash Chat
ProviderZ.ai (Zhipu)Meituan
Noometry Index51.842.1
Released2026-08-20—
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$0.15—
Output $ / M tokens$0.50—
Results tracked4019

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Category by category

Coding GLM-5.3-Flash leads

GLM-5.3-Flash: 53.1 (#31), Longcat Flash Chat: 43.5 (#87)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Coding15081471
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), Longcat Flash Chat: —

BenchmarkGLM-5.3-FlashLongcat Flash Chat
APEX-Agents52.8%—
GDP.pdf14%—

Reasoning GLM-5.3-Flash leads

GLM-5.3-Flash: 48.0 (#42), Longcat Flash Chat: 19.0 (#272)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Hard Prompts14911440
ARC-AGI-265.8%—
Kagi LLM Benchmark—43.9%
NYT Connections (extended)—17.7%
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), Longcat Flash Chat: 39.4 (#107)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Math15001442
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), Longcat Flash Chat: 40.6 (#116)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Expert15131454
GPQA Diamond90.2%—

Multimodal Not comparable

GLM-5.3-Flash: 42.8 (#27), Longcat Flash Chat: —

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Vision1296—

Multilingual GLM-5.3-Flash leads

GLM-5.3-Flash: 56.0 (#25), Longcat Flash Chat: 51.9 (#101)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Non-English14621404
LMArena Chinese15271465
LMArena French14961456
LMArena German14701408
LMArena Japanese14291373
LMArena Korean14461371
LMArena Russian14691395
LMArena Spanish14711445

Instruction Following GLM-5.3-Flash leads

GLM-5.3-Flash: 77.5 (#20), Longcat Flash Chat: 74.4 (#96)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Instruction Following14781411

Long Context GLM-5.3-Flash leads

GLM-5.3-Flash: 45.4 (#39), Longcat Flash Chat: 43.5 (#93)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Longer Query14821425

Writing & Preference GLM-5.3-Flash leads

GLM-5.3-Flash: 65.3 (#50), Longcat Flash Chat: 61.0 (#91)

BenchmarkGLM-5.3-FlashLongcat Flash Chat
LMArena Text14711427
LMArena Creative Writing14421388
LMArena Multi-Turn14671418

Frequently asked questions

Is GLM-5.3-Flash better than Longcat Flash Chat?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 42.1 on the Noometry Index.

Is GLM-5.3-Flash or Longcat Flash Chat better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 43.5 in the Noometry coding category.

How many benchmarks do GLM-5.3-Flash and Longcat Flash Chat share?

17 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Longcat Flash Chat has 19.

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