Model comparison

GLM-4.5-Air vs o3-pro

o3-pro is the stronger model overall, scoring 42.7 to 38.7 on the Noometry Index. GLM-4.5-Air costs 82× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

Last verified . 2 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.7

Rank #169 Confirmed

o3-pro OpenAI

42.7

Rank #94 Confirmed

Summary

  • They share 2 benchmarks with published results for both. GLM-4.5-Air scores higher in 1 category and o3-pro in 4 categories; 3 gaps are clear of the uncertainty.
  • The widest gap is in long context, where o3-pro leads 72.1 to 41.6.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 43% for GLM-4.5-Air and 72.1% for o3-pro.
  • GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $20 / $80 for o3-pro.
  • o3-pro accepts more context: 200K tokens versus 131K.
  • GLM-4.5-Air has downloadable open weights; the other is API-only.

Side by side

GLM-4.5-Air and o3-pro specifications
GLM-4.5-Airo3-pro
ProviderZ.ai (Zhipu)OpenAI
Noometry Index38.742.7
Released2025-07-202025-06-10
WeightsOpenProprietary
Context window131K200K
Max output98K100K
Input $ / M tokens$0.20$20
Output $ / M tokens$1.10$80
Results tracked2712

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Category by category

Coding o3-pro leads

GLM-4.5-Air: 34.5 (#225), o3-pro: 55.1 (#22)

Coding benchmarks
BenchmarkGLM-4.5-Airo3-pro
Aider Polyglot—84.9%
GSO2.9%—
WeirdML—58.2%
LMArena Coding1397—

Reasoning Too close to call

GLM-4.5-Air: 23.3 (#166), o3-pro: 24.1 (#152)

Reasoning benchmarks
BenchmarkGLM-4.5-Airo3-pro
Kagi LLM Benchmark43%72.1%
ARC-AGI-2—4.9%
ARC-AGI-1—59.3%
LMArena Hard Prompts1379—
DTBench—86.9%
LMCA—38.5%
Epoch Capabilities Index—147.43
ForecastBench59.2—

Math Not comparable

GLM-4.5-Air: 33.8 (#166), o3-pro: —

Math benchmarks
BenchmarkGLM-4.5-Airo3-pro
Omni-MATH39.1%—
LMArena Math1396—

Knowledge GLM-4.5-Air leads

GLM-4.5-Air: 34.6 (#184), o3-pro: 29.0 (#234)

Knowledge benchmarks
BenchmarkGLM-4.5-Airo3-pro
Vectara Hallucination Rate9.3%23.3%
Humanity's Last Exam8.1%—
MMLU-Pro76.2%—
Confabulations—14.2%
GPQA (HELM)59.4%—
LMArena Expert1370—

Multilingual Not comparable

GLM-4.5-Air: 49.4 (#130), o3-pro: —

Multilingual benchmarks
BenchmarkGLM-4.5-Airo3-pro
LMArena Non-English1366—
LMArena Chinese1427—
LMArena French1399—
LMArena German1376—
LMArena Japanese1348—
LMArena Korean1306—
LMArena Russian1373—
LMArena Spanish1385—

Instruction Following Not comparable

GLM-4.5-Air: 69.8 (#165), o3-pro: —

Instruction Following benchmarks
BenchmarkGLM-4.5-Airo3-pro
IFEval81.2%—
LMArena Instruction Following1353—

Long Context o3-pro leads

GLM-4.5-Air: 41.6 (#130), o3-pro: 72.1 (#1)

Long Context benchmarks
BenchmarkGLM-4.5-Airo3-pro
Fiction.LiveBench—97.2%
LMArena Longer Query1367—

Writing & Preference Too close to call

GLM-4.5-Air: 56.1 (#134), o3-pro: 57.1 (#128)

Writing & Preference benchmarks
BenchmarkGLM-4.5-Airo3-pro
LMArena Text1384—
LMArena Creative Writing1343—
Short-Story Creative Writing—84.4%
WildBench78.9%—
LMArena Multi-Turn1371—

Frequently asked questions

Is GLM-4.5-Air better than o3-pro?

o3-pro is the stronger model overall, scoring 42.7 to 38.7 on the Noometry Index. GLM-4.5-Air costs 82× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

Which is cheaper, GLM-4.5-Air or o3-pro?

GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; o3-pro lists at $20 and $80.

Is GLM-4.5-Air or o3-pro better for coding?

o3-pro scores higher on coding benchmarks: 55.1 versus 34.5 in the Noometry coding category.

Which has the bigger context window?

o3-pro does, with 200K tokens against 131K.

How many benchmarks do GLM-4.5-Air and o3-pro share?

2 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and o3-pro has 12.

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