Noometry

Model comparison

GLM-4.7 vs Llama 3.1 Nemotron 70b Instruct

GLM-4.7 is the stronger model overall, scoring 42.0 to 37.6 on the Noometry Index.

Last verified . 12 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Llama 3.1 Nemotron 70b Instruct NVIDIA

37.6

Rank #203 Confirmed

Summary

  • They share 12 benchmarks with published results for both. GLM-4.7 scores higher in 7 categories and Llama 3.1 Nemotron 70b Instruct in 1 category; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 34.1.

Side by side

GLM-4.7Llama 3.1 Nemotron 70b Instruct
ProviderZ.ai (Zhipu)NVIDIA
Noometry Index42.037.6
Released2025-12-222024-12-18
WeightsOpenOpen
Context window205K—
Max output131K—
Input $ / M tokens$0.60—
Output $ / M tokens$2.20—
Results tracked3614

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Llama 3.1 Nemotron 70b Instruct: 35.9 (#216)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Coding14541272
LMArena WebDev1435—
SciCode45.1%—
BigCodeBench Instruct—38.7%
BigCodeBench Complete—48.2%
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.5 (#103), Llama 3.1 Nemotron 70b Instruct: —

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning Too close to call

GLM-4.7: 24.3 (#164), Llama 3.1 Nemotron 70b Instruct: 25.0 (#152)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Hard Prompts14431266
SimpleBench47.7%—
CritPt1.7%—
Chess Puzzles6%—
Epoch Capabilities Index143.51—

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), Llama 3.1 Nemotron 70b Instruct: 35.5 (#182)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Math14231271
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Llama 3.1 Nemotron 70b Instruct: 34.1 (#199)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Expert14241242
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multilingual GLM-4.7 leads

GLM-4.7: 52.8 (#79), Llama 3.1 Nemotron 70b Instruct: 40.5 (#217)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Non-English14171245
LMArena Chinese14951263
LMArena Russian14231227
LMArena French1432—
LMArena German1424—
LMArena Japanese1439—
LMArena Korean1399—
LMArena Spanish1434—

Instruction Following GLM-4.7 leads

GLM-4.7: 74.4 (#95), Llama 3.1 Nemotron 70b Instruct: 65.9 (#213)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Instruction Following14111252

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), Llama 3.1 Nemotron 70b Instruct: 37.6 (#215)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Longer Query14321238
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), Llama 3.1 Nemotron 70b Instruct: 48.4 (#203)

BenchmarkGLM-4.7Llama 3.1 Nemotron 70b Instruct
LMArena Text14351283
LMArena Creative Writing14011269
LMArena Multi-Turn14461275
EQ-Bench Creative Writing1413—

Frequently asked questions

Is GLM-4.7 better than Llama 3.1 Nemotron 70b Instruct?

GLM-4.7 is the stronger model overall, scoring 42.0 to 37.6 on the Noometry Index.

Is GLM-4.7 or Llama 3.1 Nemotron 70b Instruct better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 35.9 in the Noometry coding category.

How many benchmarks do GLM-4.7 and Llama 3.1 Nemotron 70b Instruct share?

12 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Llama 3.1 Nemotron 70b Instruct has 14.

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