Noometry

Model comparison

GLM-4.5-Air vs Qwen3 32B

GLM-4.5-Air and Qwen3 32B score almost the same on the Noometry Index (38.7 vs 38.8), so choose on price, context window or the category you care about most.

Last verified . 15 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.7

Rank #169 Confirmed

Qwen3 32B Alibaba (Qwen)

38.8

Rank #166 Confirmed

Summary

  • They share 15 benchmarks with published results for both. GLM-4.5-Air scores higher in 4 categories and Qwen3 32B in 4 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where Qwen3 32B leads 40.0 to 34.6.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 43% for GLM-4.5-Air and 54.9% for Qwen3 32B.
  • GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.

Side by side

GLM-4.5-AirQwen3 32B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index38.738.8
Released2025-07-202025-04
WeightsOpenOpen
Context window131K131K
Max output98K16K
Input $ / M tokens$0.20$0.70
Output $ / M tokens$1.10$2.80
Results tracked2726

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Category by category

Coding Qwen3 32B leads

GLM-4.5-Air: 34.5 (#225), Qwen3 32B: 37.3 (#184)

BenchmarkGLM-4.5-AirQwen3 32B
LMArena Coding13971358
Aider Polyglot—40%
SciCode—35.4%
GSO2.9%—

Agentic & Tool Use Not comparable

GLM-4.5-Air: —, Qwen3 32B: 32.3 (#58)

BenchmarkGLM-4.5-AirQwen3 32B
Berkeley Function Calling Leaderboard—48.7%

Reasoning GLM-4.5-Air leads

GLM-4.5-Air: 23.3 (#166), Qwen3 32B: 19.6 (#233)

BenchmarkGLM-4.5-AirQwen3 32B
Kagi LLM Benchmark43%54.9%
LMArena Hard Prompts13791335
CritPt—0.3%
Chess Puzzles—5%
DTBench—67.5%
LMCA—17.3%
Epoch Capabilities Index—138.51
ForecastBench59.2—

Math Qwen3 32B leads

GLM-4.5-Air: 33.8 (#166), Qwen3 32B: 37.9 (#89)

BenchmarkGLM-4.5-AirQwen3 32B
LMArena Math13961399
OTIS Mock AIME 2024-2025—66.9%
Omni-MATH39.1%—

Knowledge Qwen3 32B leads

GLM-4.5-Air: 34.6 (#184), Qwen3 32B: 40.0 (#112)

BenchmarkGLM-4.5-AirQwen3 32B
Vectara Hallucination Rate9.3%5.9%
LMArena Expert13701362
GPQA Diamond—65.7%
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), Qwen3 32B: 45.8 (#162)

BenchmarkGLM-4.5-AirQwen3 32B
LMArena Non-English13661317
LMArena Chinese14271357
LMArena German13761341
LMArena Russian13731311
LMArena French1399—
LMArena Japanese1348—
LMArena Korean1306—
LMArena Spanish1385—

Instruction Following Too close to call

GLM-4.5-Air: 69.8 (#165), Qwen3 32B: 69.1 (#174)

BenchmarkGLM-4.5-AirQwen3 32B
LMArena Instruction Following13531305
IFEval81.2%—

Long Context Qwen3 32B leads

GLM-4.5-Air: 41.6 (#130), Qwen3 32B: 43.7 (#83)

BenchmarkGLM-4.5-AirQwen3 32B
LMArena Longer Query13671327
Fiction.LiveBench—74.2%

Writing & Preference GLM-4.5-Air leads

GLM-4.5-Air: 56.1 (#134), Qwen3 32B: 53.1 (#158)

BenchmarkGLM-4.5-AirQwen3 32B
LMArena Text13841340
LMArena Creative Writing13431297
LMArena Multi-Turn13711331
WildBench78.9%—

Frequently asked questions

Is GLM-4.5-Air better than Qwen3 32B?

GLM-4.5-Air and Qwen3 32B score almost the same on the Noometry Index (38.7 vs 38.8), so choose on price, context window or the category you care about most.

Which is cheaper, GLM-4.5-Air or Qwen3 32B?

GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.

Is GLM-4.5-Air or Qwen3 32B better for coding?

Qwen3 32B scores higher on coding benchmarks: 37.3 versus 34.5 in the Noometry coding category.

Which has the bigger context window?

Both accept 131K tokens.

How many benchmarks do GLM-4.5-Air and Qwen3 32B share?

15 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Qwen3 32B has 26.

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