Model comparison

GLM-5 vs Llama 3-70B

GLM-5 is the stronger model overall, scoring 46.1 to 28.8 on the Noometry Index.

Last verified . 22 shared benchmarks.

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Llama 3-70B Meta

28.8

Rank #323 Confirmed

Summary

  • They share 22 benchmarks with published results for both. GLM-5 scores higher in 9 categories and Llama 3-70B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-5 leads 46.4 to 12.8.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 80% for GLM-5 and 4.3% for Llama 3-70B.

Side by side

GLM-5 and Llama 3-70B specifications
GLM-5Llama 3-70B
ProviderZ.ai (Zhipu)Meta
Noometry Index46.128.8
Released2026-02-112024-04-18
WeightsOpenOpen
Context window205K—
Max output131K—
Input $ / M tokens$1—
Output $ / M tokens$3.20—
Results tracked4531

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Category by category

Coding GLM-5 leads

GLM-5: 49.0 (#52), Llama 3-70B: 35.8 (#218)

Coding benchmarks
BenchmarkGLM-5Llama 3-70B
LMArena Coding14611206
SWE-bench Verified72.1%—
SWE-bench Verified (bash only)72.8%—
LMArena WebDev1434—
SWE-bench Multilingual69.7%—
WeirdML48.2%—
BigCodeBench Instruct—43.6%
BigCodeBench Complete—54.5%
ALE-Bench765.62—
HumanEval+—72%
MBPP+—69%

Agentic & Tool Use GLM-5 leads

GLM-5: 31.1 (#71), Llama 3-70B: 21.1 (#139)

Agentic & Tool Use benchmarks
BenchmarkGLM-5Llama 3-70B
Terminal-Bench52.4%—
τ²-bench Airline82.5%—
τ²-bench Banking9.8%—
τ²-bench Retail73.7%—
τ²-bench Telecom86.8%—
Cybench—5%
Vending-Bench 24,432—

Reasoning GLM-5 leads

GLM-5: 27.6 (#116), Llama 3-70B: 18.0 (#288)

Reasoning benchmarks
BenchmarkGLM-5Llama 3-70B
Kagi LLM Benchmark75%35.1%
LMArena Hard Prompts14521195
Epoch Capabilities Index145.83122.93
ForecastBench6157.1
ARC-AGI-24.9%—
SimpleBench53.2%—
NYT Connections (extended)74.8%—
ARC-AGI-144.7%—
Chess Puzzles10%—
DTBench—54.2%
WinoGrande—83.5%

Math GLM-5 leads

GLM-5: 46.4 (#71), Llama 3-70B: 12.8 (#305)

Knowledge GLM-5 leads

GLM-5: 52.3 (#64), Llama 3-70B: 20.8 (#277)

Knowledge benchmarks
BenchmarkGLM-5Llama 3-70B
GPQA Diamond87.8%40.6%
LMArena Expert14541149
Vectara Hallucination Rate10.1%—
MMLU—79.3%

Multilingual GLM-5 leads

GLM-5: 53.7 (#58), Llama 3-70B: 33.6 (#251)

Multilingual benchmarks
BenchmarkGLM-5Llama 3-70B
LMArena Non-English14301142
LMArena Chinese15111114
LMArena French14551232
LMArena German14451169
LMArena Japanese14161017
LMArena Korean14231017
LMArena Russian14361159
LMArena Spanish14541241

Instruction Following GLM-5 leads

GLM-5: 75.2 (#67), Llama 3-70B: 62.5 (#238)

Instruction Following benchmarks
BenchmarkGLM-5Llama 3-70B
LMArena Instruction Following14281194

Long Context GLM-5 leads

GLM-5: 44.7 (#60), Llama 3-70B: 35.6 (#240)

Long Context benchmarks
BenchmarkGLM-5Llama 3-70B
LMArena Longer Query14461174
CL-bench18.7%—

Writing & Preference GLM-5 leads

GLM-5: 66.0 (#38), Llama 3-70B: 42.8 (#231)

Writing & Preference benchmarks
BenchmarkGLM-5Llama 3-70B
LMArena Text14461221
LMArena Creative Writing14391210
LMArena Multi-Turn14561223
EQ-Bench Creative Writing1601—

Frequently asked questions

Is GLM-5 better than Llama 3-70B?

GLM-5 is the stronger model overall, scoring 46.1 to 28.8 on the Noometry Index.

Is GLM-5 or Llama 3-70B better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 35.8 in the Noometry coding category.

How many benchmarks do GLM-5 and Llama 3-70B share?

22 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Llama 3-70B has 31.

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