Noometry

Model comparison

GLM-4.5-Air vs Qwen3.5-Flash

Qwen3.5-Flash is the stronger model overall, scoring 42.3 to 38.7 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.7

Rank #169 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.3

Rank #105 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.5-Air scores higher in 1 category and Qwen3.5-Flash in 7 categories; 6 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Qwen3.5-Flash leads 32.9 to 23.3.
  • Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
  • Qwen3.5-Flash accepts more context: 1M tokens versus 131K.
  • GLM-4.5-Air has downloadable open weights; the other is API-only.

Side by side

GLM-4.5-AirQwen3.5-Flash
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index38.742.3
Released2025-07-202026-02-23
WeightsOpenProprietary
Context window131K1M
Max output98K66K
Input $ / M tokens$0.20$0.10
Output $ / M tokens$1.10$0.40
Results tracked2732

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Category by category

Coding Too close to call

GLM-4.5-Air: 34.5 (#225), Qwen3.5-Flash: 33.9 (#234)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Coding13971412
LMArena WebDev—1243
GSO2.9%—
ALE-Bench—221.8

Agentic & Tool Use Not comparable

GLM-4.5-Air: —, Qwen3.5-Flash: —

BenchmarkGLM-4.5-AirQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

GLM-4.5-Air: 23.3 (#166), Qwen3.5-Flash: 32.9 (#63)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Hard Prompts13791404
Kagi LLM Benchmark43%—
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98
ForecastBench59.2—

Math Qwen3.5-Flash leads

GLM-4.5-Air: 33.8 (#166), Qwen3.5-Flash: 36.3 (#117)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Math13961407
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%
Omni-MATH39.1%—
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.5-Flash leads

GLM-4.5-Air: 34.6 (#184), Qwen3.5-Flash: 43.2 (#84)

BenchmarkGLM-4.5-AirQwen3.5-Flash
Vectara Hallucination Rate9.3%10.5%
LMArena Expert13701408
GPQA Diamond—82.3%
Humanity's Last Exam8.1%—
SimpleQA Verified—20.3%
MMLU-Pro76.2%—
GPQA (HELM)59.4%—

Multilingual Qwen3.5-Flash leads

GLM-4.5-Air: 49.4 (#130), Qwen3.5-Flash: 50.7 (#116)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Non-English13661385
LMArena Chinese14271446
LMArena French13991412
LMArena German13761389
LMArena Japanese13481369
LMArena Korean13061344
LMArena Russian13731379
LMArena Spanish13851399

Instruction Following Qwen3.5-Flash leads

GLM-4.5-Air: 69.8 (#165), Qwen3.5-Flash: 72.8 (#133)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Instruction Following13531374
IFEval81.2%—

Long Context Too close to call

GLM-4.5-Air: 41.6 (#130), Qwen3.5-Flash: 42.4 (#119)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Longer Query13671392

Writing & Preference Qwen3.5-Flash leads

GLM-4.5-Air: 56.1 (#134), Qwen3.5-Flash: 58.2 (#117)

BenchmarkGLM-4.5-AirQwen3.5-Flash
LMArena Text13841397
LMArena Creative Writing13431343
LMArena Multi-Turn13711393
WildBench78.9%—

Frequently asked questions

Is GLM-4.5-Air better than Qwen3.5-Flash?

Qwen3.5-Flash is the stronger model overall, scoring 42.3 to 38.7 on the Noometry Index.

Which is cheaper, GLM-4.5-Air or Qwen3.5-Flash?

Qwen3.5-Flash is cheaper. It lists at $0.10 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 Qwen3.5-Flash better for coding?

They score almost the same on coding (34.5 vs 33.9); test both on your own repository before choosing.

Which has the bigger context window?

Qwen3.5-Flash does, with 1M tokens against 131K.

How many benchmarks do GLM-4.5-Air and Qwen3.5-Flash share?

18 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Qwen3.5-Flash has 32.

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