Noometry

Model comparison

GLM-4.5-Air vs Llama 3.2 1B

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 20.1 on the Noometry Index. Llama 3.2 1B costs 6.0× less per token, which makes it the better buy when GLM-4.5-Air's lead doesn't matter for your workload.

Last verified . 13 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.9

Rank #177 Confirmed

Llama 3.2 1B Meta

20.1

Rank #354 Confirmed

Summary

  • They share 13 benchmarks with published results for both. GLM-4.5-Air scores higher in 8 categories and Llama 3.2 1B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GLM-4.5-Air leads 55.9 to 21.3.
  • Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
  • GLM-4.5-Air accepts more context: 131K tokens versus 60K.

Side by side

GLM-4.5-AirLlama 3.2 1B
ProviderZ.ai (Zhipu)Meta
Noometry Index38.920.1
Released2025-07-202024-09-24
WeightsOpenOpen
Context window131K60K
Max output98K54K
Input $ / M tokens$0.20$0.027
Output $ / M tokens$1.10$0.20
Results tracked2722

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Category by category

Coding GLM-4.5-Air leads

GLM-4.5-Air: 33.3 (#259), Llama 3.2 1B: 21.1 (#338)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Coding13971070
GSO2.9%—
BigCodeBench Instruct—8.2%
BigCodeBench Complete—11.3%

Agentic & Tool Use Not comparable

GLM-4.5-Air: —, Llama 3.2 1B: 14.6 (#150)

BenchmarkGLM-4.5-AirLlama 3.2 1B
Berkeley Function Calling Leaderboard—10.8%
BALROG—6.6%

Reasoning GLM-4.5-Air leads

GLM-4.5-Air: 24.1 (#166), Llama 3.2 1B: 16.2 (#308)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Hard Prompts13791044
Kagi LLM Benchmark43%—
Chess Puzzles—0%
Epoch Capabilities Index—101.99
ForecastBench59.2—

Math GLM-4.5-Air leads

GLM-4.5-Air: 36.2 (#170), Llama 3.2 1B: 10.4 (#313)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Math13961086
OTIS Mock AIME 2024-2025—0.6%
Omni-MATH39.1%—

Knowledge GLM-4.5-Air leads

GLM-4.5-Air: 35.0 (#191), Llama 3.2 1B: 7.2 (#312)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Expert13701007
GPQA Diamond—23.9%
Humanity's Last Exam8.1%—
MMLU-Pro76.2%—
Vectara Hallucination Rate9.3%—
GPQA (HELM)59.4%—

Multilingual GLM-4.5-Air leads

GLM-4.5-Air: 49.1 (#135), Llama 3.2 1B: 23.8 (#292)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Non-English1366973
LMArena Chinese1426959
LMArena German13771014
LMArena Russian1373941
LMArena French1399—
LMArena Japanese1348—
LMArena Korean1308—
LMArena Spanish1386—

Instruction Following GLM-4.5-Air leads

GLM-4.5-Air: 69.6 (#171), Llama 3.2 1B: 52.4 (#290)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Instruction Following13541031
IFEval81.2%—

Long Context GLM-4.5-Air leads

GLM-4.5-Air: 41.6 (#135), Llama 3.2 1B: 31.9 (#274)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Longer Query13661050

Writing & Preference GLM-4.5-Air leads

GLM-4.5-Air: 55.9 (#139), Llama 3.2 1B: 21.3 (#310)

BenchmarkGLM-4.5-AirLlama 3.2 1B
LMArena Text13841055
LMArena Creative Writing13431033
LMArena Multi-Turn13711030
EQ-Bench Creative Writing—200
WildBench78.9%—

Frequently asked questions

Is GLM-4.5-Air better than Llama 3.2 1B?

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 20.1 on the Noometry Index. Llama 3.2 1B costs 6.0× 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 Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; GLM-4.5-Air lists at $0.20 and $1.10.

Is GLM-4.5-Air or Llama 3.2 1B better for coding?

GLM-4.5-Air scores higher on coding benchmarks: 33.3 versus 21.1 in the Noometry coding category.

Which has the bigger context window?

GLM-4.5-Air does, with 131K tokens against 60K.

How many benchmarks do GLM-4.5-Air and Llama 3.2 1B share?

13 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Llama 3.2 1B has 22.

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