Noometry

Model comparison

GLM-4.5-Air vs Llama 3.1-70B

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 29.6 on the Noometry Index.

Last verified . 22 shared benchmarks.

GLM-4.5-Air Z.ai (Zhipu)

38.9

Rank #177 Confirmed

Llama 3.1-70B Meta

29.6

Rank #308 Confirmed

Summary

  • They share 22 benchmarks with published results for both. GLM-4.5-Air scores higher in 8 categories and Llama 3.1-70B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.5-Air leads 36.2 to 13.5.
  • The biggest single-benchmark swing is Omni-MATH: 39.1% for GLM-4.5-Air and 21% for Llama 3.1-70B.
  • Llama 3.1-70B is cheaper at $0.40 / $0.40 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 128K.

Side by side

GLM-4.5-AirLlama 3.1-70B
ProviderZ.ai (Zhipu)Meta
Noometry Index38.929.6
Released2025-07-202024-07-23
WeightsOpenOpen
Context window131K128K
Max output98K4K
Input $ / M tokens$0.20$0.40
Output $ / M tokens$1.10$0.40
Results tracked2735

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Category by category

Coding GLM-4.5-Air leads

GLM-4.5-Air: 33.3 (#259), Llama 3.1-70B: 30.3 (#296)

BenchmarkGLM-4.5-AirLlama 3.1-70B
LMArena Coding13971260
GSO2.9%—
WeirdML—9%
BigCodeBench Instruct—46.1%
BigCodeBench Complete—54.8%

Agentic & Tool Use Not comparable

GLM-4.5-Air: —, Llama 3.1-70B: 25.1 (#112)

BenchmarkGLM-4.5-AirLlama 3.1-70B
TheAgentCompany—6.9%
BALROG—27.9%

Reasoning GLM-4.5-Air leads

GLM-4.5-Air: 24.1 (#166), Llama 3.1-70B: 21.6 (#220)

BenchmarkGLM-4.5-AirLlama 3.1-70B
LMArena Hard Prompts13791241
Kagi LLM Benchmark43%—
DTBench—60%
LMCA—14.8%
Epoch Capabilities Index—125.92
ForecastBench59.2—

Math GLM-4.5-Air leads

GLM-4.5-Air: 36.2 (#170), Llama 3.1-70B: 13.5 (#304)

BenchmarkGLM-4.5-AirLlama 3.1-70B
Omni-MATH39.1%21%
LMArena Math13961252
OTIS Mock AIME 2024-2025—3.6%
MATH Level 5—36.7%

Knowledge GLM-4.5-Air leads

GLM-4.5-Air: 35.0 (#191), Llama 3.1-70B: 24.2 (#269)

BenchmarkGLM-4.5-AirLlama 3.1-70B
MMLU-Pro76.2%65.3%
GPQA (HELM)59.4%42.6%
LMArena Expert13701209
GPQA Diamond—44.2%
Humanity's Last Exam8.1%—
Vectara Hallucination Rate9.3%—
MMLU—80.1%

Multilingual GLM-4.5-Air leads

GLM-4.5-Air: 49.1 (#135), Llama 3.1-70B: 38.8 (#225)

BenchmarkGLM-4.5-AirLlama 3.1-70B
LMArena Non-English13661219
LMArena Chinese14261215
LMArena French13991261
LMArena German13771222
LMArena Japanese13481132
LMArena Korean13081140
LMArena Russian13731234
LMArena Spanish13861253

Instruction Following GLM-4.5-Air leads

GLM-4.5-Air: 69.6 (#171), Llama 3.1-70B: 65.3 (#223)

BenchmarkGLM-4.5-AirLlama 3.1-70B
IFEval81.2%82.1%
LMArena Instruction Following13541231

Long Context GLM-4.5-Air leads

GLM-4.5-Air: 41.6 (#135), Llama 3.1-70B: 37.6 (#214)

BenchmarkGLM-4.5-AirLlama 3.1-70B
LMArena Longer Query13661241

Writing & Preference GLM-4.5-Air leads

GLM-4.5-Air: 55.9 (#139), Llama 3.1-70B: 35.4 (#267)

BenchmarkGLM-4.5-AirLlama 3.1-70B
LMArena Text13841261
LMArena Creative Writing13431232
WildBench78.9%75.8%
LMArena Multi-Turn13711256
EQ-Bench Creative Writing—784

Frequently asked questions

Is GLM-4.5-Air better than Llama 3.1-70B?

GLM-4.5-Air is the stronger model overall, scoring 38.9 to 29.6 on the Noometry Index.

Which is cheaper, GLM-4.5-Air or Llama 3.1-70B?

Llama 3.1-70B is cheaper. It lists at $0.40 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 Llama 3.1-70B better for coding?

GLM-4.5-Air scores higher on coding benchmarks: 33.3 versus 30.3 in the Noometry coding category.

Which has the bigger context window?

GLM-4.5-Air does, with 131K tokens against 128K.

How many benchmarks do GLM-4.5-Air and Llama 3.1-70B share?

22 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Llama 3.1-70B has 35.

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