Noometry

Model comparison

GLM-4.5 vs Llama 3.1-405B

GLM-4.5 is the stronger model overall, scoring 42.0 to 30.7 on the Noometry Index.

Last verified . 21 shared benchmarks.

GLM-4.5 Z.ai (Zhipu)

42.0

Rank #122 Confirmed

Llama 3.1-405B Meta

30.7

Rank #288 Confirmed

Summary

  • They share 21 benchmarks with published results for both. GLM-4.5 scores higher in 7 categories and Llama 3.1-405B in 1 category; 7 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.5 leads 39.0 to 18.4.
  • The biggest single-benchmark swing is WeirdML: 40.6% for GLM-4.5 and 21.4% for Llama 3.1-405B.

Side by side

GLM-4.5Llama 3.1-405B
ProviderZ.ai (Zhipu)Meta
Noometry Index42.030.7
Released2025-07-272024-07-23
WeightsOpenOpen
Context window131K—
Max output98K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked2742

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Category by category

Coding GLM-4.5 leads

GLM-4.5: 41.4 (#125), Llama 3.1-405B: 33.1 (#262)

BenchmarkGLM-4.5Llama 3.1-405B
WeirdML40.6%21.4%
LMArena Coding14341291
SWE-bench Verified (bash only)54.2%—
ALE-Bench344.82—
AlgoTune1.52—

Agentic & Tool Use Not comparable

GLM-4.5: —, Llama 3.1-405B: 21.0 (#140)

BenchmarkGLM-4.5Llama 3.1-405B
TheAgentCompany—7.4%
Cybench—7.5%

Reasoning GLM-4.5 leads

GLM-4.5: 28.6 (#100), Llama 3.1-405B: 16.8 (#300)

BenchmarkGLM-4.5Llama 3.1-405B
Kagi LLM Benchmark57.9%45%
LMArena Hard Prompts14291269
SimpleBench—23%
DTBench—61.4%
BIG-Bench Hard—82.9%
Epoch Capabilities Index—128.75
ForecastBench—59.9
HellaSwag—89.2%
PIQA—85.9%
WinoGrande—89.2%

Math GLM-4.5 leads

GLM-4.5: 39.0 (#116), Llama 3.1-405B: 18.4 (#290)

BenchmarkGLM-4.5Llama 3.1-405B
LMArena Math14271281
OTIS Mock AIME 2024-2025—9.7%
Omni-MATH—24.9%
MATH Level 5—49.8%

Knowledge GLM-4.5 leads

GLM-4.5: 35.9 (#179), Llama 3.1-405B: 30.4 (#227)

BenchmarkGLM-4.5Llama 3.1-405B
Confabulations11.3%17.6%
LMArena Expert14331243
GPQA Diamond—50.9%
Humanity's Last Exam8.3%—
MMLU-Pro—72.3%
GPQA (HELM)—52.2%
ARC (AI2) Challenge—95.3%
MMLU—84.5%
TriviaQA—82.7%

Multilingual GLM-4.5 leads

GLM-4.5: 52.8 (#77), Llama 3.1-405B: 40.7 (#214)

BenchmarkGLM-4.5Llama 3.1-405B
LMArena Non-English14171248
LMArena Chinese14651242
LMArena French14181279
LMArena German14071252
LMArena Japanese14151208
LMArena Korean13801184
LMArena Russian14141265
LMArena Spanish14541260

Instruction Following GLM-4.5 leads

GLM-4.5: 74.1 (#104), Llama 3.1-405B: 65.9 (#214)

BenchmarkGLM-4.5Llama 3.1-405B
LMArena Instruction Following14041259
IFEval—81.1%

Long Context Too close to call

GLM-4.5: 38.2 (#201), Llama 3.1-405B: 38.4 (#197)

BenchmarkGLM-4.5Llama 3.1-405B
LMArena Longer Query14121266
Fiction.LiveBench58.3%—

Writing & Preference GLM-4.5 leads

GLM-4.5: 57.5 (#127), Llama 3.1-405B: 38.9 (#251)

BenchmarkGLM-4.5Llama 3.1-405B
LMArena Text14301284
LMArena Creative Writing13951262
EQ-Bench Creative Writing1343870
LMArena Multi-Turn14151297
Short-Story Creative Writing73.4%—
WildBench—78.3%

Frequently asked questions

Is GLM-4.5 better than Llama 3.1-405B?

GLM-4.5 is the stronger model overall, scoring 42.0 to 30.7 on the Noometry Index.

Is GLM-4.5 or Llama 3.1-405B better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 33.1 in the Noometry coding category.

How many benchmarks do GLM-4.5 and Llama 3.1-405B share?

21 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 3.1-405B has 42.

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