Model comparison

GLM-5.2 vs Longcat Flash Chat

GLM-5.2 is the stronger model overall, scoring 51.1 to 42.1 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-5.2 Z.ai (Zhipu)

51.1

Rank #44 Confirmed

Longcat Flash Chat Meituan

42.1

Rank #120 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-5.2 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-5.2 leads 42.3 to 19.0.
  • The biggest single-benchmark swing is NYT Connections (extended): 74.3% for GLM-5.2 and 17.7% for Longcat Flash Chat.

Side by side

GLM-5.2 and Longcat Flash Chat specifications
GLM-5.2Longcat Flash Chat
ProviderZ.ai (Zhipu)Meituan
Noometry Index51.142.1
Released2026-06-13—
WeightsOpenOpen
Context window1M—
Max output131K—
Input $ / M tokens$1.40—
Output $ / M tokens$4.40—
Results tracked5119

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Category by category

Coding GLM-5.2 leads

GLM-5.2: 51.3 (#41), Longcat Flash Chat: 43.5 (#87)

Coding benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Coding14851471
SWE-bench Verified78.7%—
DeepSWE43.8%—
FrontierCode24.5%—
LMArena WebDev1603—
SciCode50.5%—
WeirdML70.1%—
ALE-Bench1,047—

Agentic & Tool Use Not comparable

GLM-5.2: 32.4 (#63), Longcat Flash Chat: —

Agentic & Tool Use benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
APEX-Agents45.2%—
τ²-bench Banking37.1%—
PostTrainBench31.7%—
GBAEval0%—
Vending-Bench 28,314—

Reasoning GLM-5.2 leads

GLM-5.2: 42.3 (#52), Longcat Flash Chat: 19.0 (#272)

Reasoning benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
Kagi LLM Benchmark62.6%43.9%
NYT Connections (extended)74.3%17.7%
LMArena Hard Prompts14801440
ARC-AGI-222.8%—
SimpleBench58.8%—
ARC-AGI-177%—
CritPt20.9%—
Chess Puzzles21%—
EBR-Bench9.5%—
Mystery Game Puzzles19%—
DTBench93.6%—
LMCA45.8%—
Surface Evolver Bench55.6%—
Epoch Capabilities Index151.78—

Math GLM-5.2 leads

GLM-5.2: 55.7 (#43), Longcat Flash Chat: 39.4 (#107)

Math benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Math14821442
FrontierMath (Tiers 1-3)59.2%—
FrontierMath Tier 429.3%—
MathArena Final-Answer Competitions67.6%—
OTIS Mock AIME 2024-202586.4%—
ProofBench35%—

Knowledge GLM-5.2 leads

GLM-5.2: 57.1 (#40), Longcat Flash Chat: 40.6 (#116)

Knowledge benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Expert14861454
GPQA Diamond91.9%—
SimpleQA Verified34.2%—

Multilingual GLM-5.2 leads

GLM-5.2: 55.8 (#26), Longcat Flash Chat: 51.9 (#101)

Multilingual benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Non-English14591404
LMArena Chinese15191465
LMArena French14791456
LMArena German14681408
LMArena Japanese14511373
LMArena Korean14451371
LMArena Russian14661395
LMArena Spanish14771445

Instruction Following GLM-5.2 leads

GLM-5.2: 76.9 (#34), Longcat Flash Chat: 74.4 (#96)

Instruction Following benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Instruction Following14651411

Long Context GLM-5.2 leads

GLM-5.2: 45.3 (#43), Longcat Flash Chat: 43.5 (#93)

Long Context benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Longer Query14791425

Writing & Preference GLM-5.2 leads

GLM-5.2: 70.4 (#21), Longcat Flash Chat: 61.0 (#91)

Writing & Preference benchmarks
BenchmarkGLM-5.2Longcat Flash Chat
LMArena Text14701427
LMArena Creative Writing14621388
LMArena Multi-Turn14691418
EQ-Bench Creative Writing1757—
EQ-Bench 41222—

Frequently asked questions

Is GLM-5.2 better than Longcat Flash Chat?

GLM-5.2 is the stronger model overall, scoring 51.1 to 42.1 on the Noometry Index.

Is GLM-5.2 or Longcat Flash Chat better for coding?

GLM-5.2 scores higher on coding benchmarks: 51.3 versus 43.5 in the Noometry coding category.

How many benchmarks do GLM-5.2 and Longcat Flash Chat share?

19 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Longcat Flash Chat has 19.

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