Model comparison

GLM-4.5-Air vs Qwen3.5-9B

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 33.8 on the Noometry Index. Qwen3.5-9B costs 3.8× less per token, which makes it the better buy when GLM-4.5-Air's lead doesn't matter for your workload.

Last verified . 0 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.9

Rank #177 Confirmed

Qwen3.5-9B Alibaba (Qwen)

33.8

Rank #236 Confirmed

Summary

  • The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 35.0.
  • Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
  • Qwen3.5-9B accepts more context: 262K tokens versus 131K.

Side by side

GLM-4.5-Air and Qwen3.5-9B specifications
GLM-4.5-AirQwen3.5-9B
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index38.933.8
Released2025-07-202026-02-23
WeightsOpenOpen
Context window131K262K
Max output98K66K
Input $ / M tokens$0.20$0.10
Output $ / M tokens$1.10$0.15
Results tracked2710

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Category by category

Coding Qwen3.5-9B leads

GLM-4.5-Air: 33.3 (#259), Qwen3.5-9B: 35.9 (#217)

Coding benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
SciCode—27.5%
GSO2.9%—
LMArena Coding1397—

Agentic & Tool Use Not comparable

GLM-4.5-Air: —, Qwen3.5-9B: 14.5 (#151)

Agentic & Tool Use benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
Terminal-Bench—9.2%

Reasoning Too close to call

GLM-4.5-Air: 24.1 (#166), Qwen3.5-9B: 23.1 (#182)

Reasoning benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
Kagi LLM Benchmark43%—
CritPt—0.3%
Chess Puzzles—12%
LMArena Hard Prompts1379—
DTBench—71.2%
LMCA—24.5%
Epoch Capabilities Index—139.46
ForecastBench59.2—

Math GLM-4.5-Air leads

GLM-4.5-Air: 36.2 (#170), Qwen3.5-9B: 34.8 (#192)

Math benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
MathArena Final-Answer Competitions—48.5%
OTIS Mock AIME 2024-2025—61.7%
Omni-MATH39.1%—
LMArena Math1396—

Knowledge Qwen3.5-9B leads

GLM-4.5-Air: 35.0 (#191), Qwen3.5-9B: 46.0 (#84)

Knowledge benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
GPQA Diamond—79%
Humanity's Last Exam8.1%—
MMLU-Pro76.2%—
Vectara Hallucination Rate9.3%—
GPQA (HELM)59.4%—
LMArena Expert1370—

Multilingual Not comparable

GLM-4.5-Air: 49.1 (#135), Qwen3.5-9B: —

Multilingual benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
LMArena Non-English1366—
LMArena Chinese1426—
LMArena French1399—
LMArena German1377—
LMArena Japanese1348—
LMArena Korean1308—
LMArena Russian1373—
LMArena Spanish1386—

Instruction Following Not comparable

GLM-4.5-Air: 69.6 (#171), Qwen3.5-9B: —

Instruction Following benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
IFEval81.2%—
LMArena Instruction Following1354—

Long Context Not comparable

GLM-4.5-Air: 41.6 (#135), Qwen3.5-9B: —

Long Context benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
LMArena Longer Query1366—

Writing & Preference Not comparable

GLM-4.5-Air: 55.9 (#139), Qwen3.5-9B: —

Writing & Preference benchmarks
BenchmarkGLM-4.5-AirQwen3.5-9B
LMArena Text1384—
LMArena Creative Writing1343—
WildBench78.9%—
LMArena Multi-Turn1371—

Frequently asked questions

Is GLM-4.5-Air better than Qwen3.5-9B?

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 33.8 on the Noometry Index. Qwen3.5-9B costs 3.8× less per token, which makes it the better buy when GLM-4.5-Air's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5-Air or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GLM-4.5-Air lists at $0.20 and $1.10.

Is GLM-4.5-Air or Qwen3.5-9B better for coding?

Qwen3.5-9B scores higher on coding benchmarks: 35.9 versus 33.3 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 131K.

How many benchmarks do GLM-4.5-Air and Qwen3.5-9B share?

0 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Qwen3.5-9B has 10.

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