Noometry

Model comparison

GLM-4.7-Flash vs Llama 3.1-405B

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.7 on the Noometry Index.

Last verified . 19 shared benchmarks.

GLM-4.7-Flash Z.ai (Zhipu)

38.8

Rank #180 Confirmed

Llama 3.1-405B Meta

30.7

Rank #288 Confirmed

Summary

  • They share 19 benchmarks with published results for both. GLM-4.7-Flash scores higher in 8 categories and Llama 3.1-405B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.7-Flash leads 36.1 to 18.4.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 9.7% for Llama 3.1-405B.

Side by side

GLM-4.7-FlashLlama 3.1-405B
ProviderZ.ai (Zhipu)Meta
Noometry Index38.830.7
Released2026-01-192024-07-23
WeightsOpenOpen
Context window200K—
Max output131K—
Input $ / M tokens$0.06—
Output $ / M tokens$0.40—
Results tracked2142

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Category by category

Coding GLM-4.7-Flash leads

GLM-4.7-Flash: 40.6 (#135), Llama 3.1-405B: 33.1 (#262)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
LMArena Coding13831291
WeirdML—21.4%

Agentic & Tool Use Not comparable

GLM-4.7-Flash: —, Llama 3.1-405B: 21.0 (#140)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
TheAgentCompany—7.4%
Cybench—7.5%

Reasoning GLM-4.7-Flash leads

GLM-4.7-Flash: 20.9 (#229), Llama 3.1-405B: 16.8 (#300)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
LMArena Hard Prompts13561269
SimpleBench—23%
Kagi LLM Benchmark—45%
Chess Puzzles0%—
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-4.7-Flash leads

GLM-4.7-Flash: 36.1 (#173), Llama 3.1-405B: 18.4 (#290)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
OTIS Mock AIME 2024-202558.3%9.7%
LMArena Math13551281
Omni-MATH—24.9%
MATH Level 5—49.8%

Knowledge GLM-4.7-Flash leads

GLM-4.7-Flash: 35.5 (#184), Llama 3.1-405B: 30.4 (#227)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
GPQA Diamond60.5%50.9%
LMArena Expert13571243
MMLU-Pro—72.3%
Confabulations—17.6%
Vectara Hallucination Rate9.3%—
GPQA (HELM)—52.2%
ARC (AI2) Challenge—95.3%
MMLU—84.5%
TriviaQA—82.7%

Multilingual GLM-4.7-Flash leads

GLM-4.7-Flash: 46.5 (#158), Llama 3.1-405B: 40.7 (#214)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
LMArena Non-English13301248
LMArena Chinese14031242
LMArena French13321279
LMArena German13371252
LMArena Korean12831184
LMArena Russian13321265
LMArena Spanish13501260
LMArena Japanese—1208

Instruction Following GLM-4.7-Flash leads

GLM-4.7-Flash: 70.1 (#167), Llama 3.1-405B: 65.9 (#214)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
LMArena Instruction Following13271259
IFEval—81.1%

Long Context GLM-4.7-Flash leads

GLM-4.7-Flash: 40.9 (#148), Llama 3.1-405B: 38.4 (#197)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
LMArena Longer Query13451266

Writing & Preference GLM-4.7-Flash leads

GLM-4.7-Flash: 47.4 (#210), Llama 3.1-405B: 38.9 (#251)

BenchmarkGLM-4.7-FlashLlama 3.1-405B
LMArena Text13511284
LMArena Creative Writing12971262
EQ-Bench Creative Writing1125870
LMArena Multi-Turn13421297
WildBench—78.3%

Frequently asked questions

Is GLM-4.7-Flash better than Llama 3.1-405B?

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 30.7 on the Noometry Index.

Is GLM-4.7-Flash or Llama 3.1-405B better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 33.1 in the Noometry coding category.

How many benchmarks do GLM-4.7-Flash and Llama 3.1-405B share?

19 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Llama 3.1-405B has 42.

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