Model comparison

GLM-4.7 vs Longcat Flash Chat

GLM-4.7 and Longcat Flash Chat score almost the same on the Noometry Index (41.7 vs 41.5), so choose on price, context window or the category you care about most.

Last verified . 17 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

Longcat Flash Chat Meituan

41.5

Rank #121 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-4.7 scores higher in 6 categories and Longcat Flash Chat in 2 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 40.0.

Side by side

GLM-4.7 and Longcat Flash Chat specifications
GLM-4.7Longcat Flash Chat
ProviderZ.ai (Zhipu)Meituan
Noometry Index41.741.5
Released2025-12-22—
WeightsOpenOpen
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked3619

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Category by category

Coding Too close to call

GLM-4.7: 43.6 (#74), Longcat Flash Chat: 42.9 (#85)

Coding benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Coding14541471
LMArena WebDev1435—
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.4 (#96), Longcat Flash Chat: —

Agentic & Tool Use benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 23.7 (#161), Longcat Flash Chat: 18.3 (#267)

Reasoning benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Hard Prompts14431440
SimpleBench47.7%—
Kagi LLM Benchmark—43.9%
NYT Connections (extended)—17.7%
CritPt1.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.53—

Math GLM-4.7 leads

GLM-4.7: 37.7 (#92), Longcat Flash Chat: 36.6 (#107)

Math benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Math14231441
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#74), Longcat Flash Chat: 40.0 (#111)

Knowledge benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Expert14241454
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multilingual Too close to call

GLM-4.7: 53.0 (#75), Longcat Flash Chat: 52.1 (#95)

Multilingual benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Non-English14171404
LMArena Chinese14951465
LMArena French14321457
LMArena German14261409
LMArena Japanese14391373
LMArena Korean14011372
LMArena Russian14231396
LMArena Spanish14331445

Instruction Following Too close to call

GLM-4.7: 74.6 (#90), Longcat Flash Chat: 74.6 (#92)

Instruction Following benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Instruction Following14111411

Long Context Too close to call

GLM-4.7: 42.8 (#111), Longcat Flash Chat: 43.5 (#89)

Long Context benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Longer Query14321425
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference Too close to call

GLM-4.7: 61.1 (#89), Longcat Flash Chat: 61.2 (#88)

Writing & Preference benchmarks
BenchmarkGLM-4.7Longcat Flash Chat
LMArena Text14361427
LMArena Creative Writing14011388
LMArena Multi-Turn14461418
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than Longcat Flash Chat?

GLM-4.7 and Longcat Flash Chat score almost the same on the Noometry Index (41.7 vs 41.5), so choose on price, context window or the category you care about most.

Is GLM-4.7 or Longcat Flash Chat better for coding?

They score almost the same on coding (43.6 vs 42.9); test both on your own repository before choosing.

How many benchmarks do GLM-4.7 and Longcat Flash Chat share?

17 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Longcat Flash Chat has 19.

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