Noometry

Model comparison

GLM-4.7 vs Llama 3-70B

GLM-4.7 is the stronger model overall, scoring 42.0 to 28.8 on the Noometry Index.

Last verified . 20 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Llama 3-70B Meta

28.8

Rank #323 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GLM-4.7 scores higher in 9 categories and Llama 3-70B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 20.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 83.3% for GLM-4.7 and 4.3% for Llama 3-70B.

Side by side

GLM-4.7Llama 3-70B
ProviderZ.ai (Zhipu)Meta
Noometry Index42.028.8
Released2025-12-222024-04-18
WeightsOpenOpen
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked3631

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Llama 3-70B: 35.8 (#218)

BenchmarkGLM-4.7Llama 3-70B
LMArena Coding14541206
LMArena WebDev1435—
SciCode45.1%—
BigCodeBench Instruct—43.6%
BigCodeBench Complete—54.5%
ALE-Bench399.48—
HumanEval+—72%
MBPP+—69%

Agentic & Tool Use GLM-4.7 leads

GLM-4.7: 26.5 (#103), Llama 3-70B: 21.1 (#139)

BenchmarkGLM-4.7Llama 3-70B
Terminal-Bench33.4%—
Cybench—5%
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), Llama 3-70B: 18.0 (#288)

BenchmarkGLM-4.7Llama 3-70B
LMArena Hard Prompts14431195
Epoch Capabilities Index143.51122.93
SimpleBench47.7%—
Kagi LLM Benchmark—35.1%
CritPt1.7%—
Chess Puzzles6%—
DTBench—54.2%
ForecastBench—57.1
WinoGrande—83.5%

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), Llama 3-70B: 12.8 (#305)

BenchmarkGLM-4.7Llama 3-70B
OTIS Mock AIME 2024-202583.3%4.3%
LMArena Math14231218
ProofBench6%—
MATH Level 5—22.6%
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Llama 3-70B: 20.8 (#277)

BenchmarkGLM-4.7Llama 3-70B
GPQA Diamond83.3%40.6%
LMArena Expert14241149
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—
MMLU—79.3%

Multilingual GLM-4.7 leads

GLM-4.7: 52.8 (#79), Llama 3-70B: 33.6 (#251)

BenchmarkGLM-4.7Llama 3-70B
LMArena Non-English14171142
LMArena Chinese14951114
LMArena French14321232
LMArena German14241169
LMArena Japanese14391017
LMArena Korean13991017
LMArena Russian14231159
LMArena Spanish14341241

Instruction Following GLM-4.7 leads

GLM-4.7: 74.4 (#95), Llama 3-70B: 62.5 (#238)

BenchmarkGLM-4.7Llama 3-70B
LMArena Instruction Following14111194

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), Llama 3-70B: 35.6 (#240)

BenchmarkGLM-4.7Llama 3-70B
LMArena Longer Query14321174
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), Llama 3-70B: 42.8 (#231)

BenchmarkGLM-4.7Llama 3-70B
LMArena Text14351221
LMArena Creative Writing14011210
LMArena Multi-Turn14461223
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than Llama 3-70B?

GLM-4.7 is the stronger model overall, scoring 42.0 to 28.8 on the Noometry Index.

Is GLM-4.7 or Llama 3-70B better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 35.8 in the Noometry coding category.

How many benchmarks do GLM-4.7 and Llama 3-70B share?

20 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Llama 3-70B has 31.

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