Noometry

Model comparison

GLM-4.5-Air vs GLM-4.7-Flash

GLM-4.5-Air and GLM-4.7-Flash score almost the same on the Noometry Index (38.7 vs 38.4), so choose on price, context window or the category you care about most.

Last verified . 17 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.7

Rank #169 Confirmed

GLM-4.7-Flash Z.ai (Zhipu)

38.4

Rank #175 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GLM-4.5-Air scores higher in 4 categories and GLM-4.7-Flash in 4 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.5-Air leads 56.1 to 47.7.
  • GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
  • GLM-4.7-Flash accepts more context: 200K tokens versus 131K.

Side by side

GLM-4.5-AirGLM-4.7-Flash
ProviderZ.ai (Zhipu)Z.ai (Zhipu)
Noometry Index38.738.4
Released2025-07-202026-01-19
WeightsOpenOpen
Context window131K200K
Max output98K131K
Input $ / M tokens$0.20$0.06
Output $ / M tokens$1.10$0.40
Results tracked2721

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.5-Air: 34.5 (#225), GLM-4.7-Flash: 40.0 (#133)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Coding13971383
GSO2.9%—

Reasoning GLM-4.5-Air leads

GLM-4.5-Air: 23.3 (#166), GLM-4.7-Flash: 20.2 (#224)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Hard Prompts13791356
Kagi LLM Benchmark43%—
Chess Puzzles—0%
ForecastBench59.2—

Math Too close to call

GLM-4.5-Air: 33.8 (#166), GLM-4.7-Flash: 34.4 (#159)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Math13961354
OTIS Mock AIME 2024-2025—58.3%
Omni-MATH39.1%—

Knowledge Too close to call

GLM-4.5-Air: 34.6 (#184), GLM-4.7-Flash: 35.4 (#177)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
Vectara Hallucination Rate9.3%9.3%
LMArena Expert13701357
GPQA Diamond—60.5%
Humanity's Last Exam8.1%—
MMLU-Pro76.2%—
GPQA (HELM)59.4%—

Multilingual GLM-4.5-Air leads

GLM-4.5-Air: 49.4 (#130), GLM-4.7-Flash: 46.8 (#152)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Non-English13661331
LMArena Chinese14271403
LMArena French13991332
LMArena German13761336
LMArena Korean13061284
LMArena Russian13731333
LMArena Spanish13851351
LMArena Japanese1348—

Instruction Following Too close to call

GLM-4.5-Air: 69.8 (#165), GLM-4.7-Flash: 70.3 (#162)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Instruction Following13531327
IFEval81.2%—

Long Context Too close to call

GLM-4.5-Air: 41.6 (#130), GLM-4.7-Flash: 40.9 (#143)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Longer Query13671345

Writing & Preference GLM-4.5-Air leads

GLM-4.5-Air: 56.1 (#134), GLM-4.7-Flash: 47.7 (#206)

BenchmarkGLM-4.5-AirGLM-4.7-Flash
LMArena Text13841351
LMArena Creative Writing13431297
LMArena Multi-Turn13711342
EQ-Bench Creative Writing—1125
WildBench78.9%—

Frequently asked questions

Is GLM-4.5-Air better than GLM-4.7-Flash?

GLM-4.5-Air and GLM-4.7-Flash score almost the same on the Noometry Index (38.7 vs 38.4), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5-Air or GLM-4.7-Flash?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GLM-4.5-Air lists at $0.20 and $1.10.

Is GLM-4.5-Air or GLM-4.7-Flash better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.0 versus 34.5 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7-Flash does, with 200K tokens against 131K.

How many benchmarks do GLM-4.5-Air and GLM-4.7-Flash share?

17 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and GLM-4.7-Flash has 21.

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