Model comparison

GLM-4.6V vs Llama 3-70B

GLM-4.6V is the stronger model overall, scoring 40.9 to 28.5 on the Noometry Index.

Last verified . 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

40.9

Rank #133 Confirmed

Llama 3-70B Meta

28.5

Rank #317 Confirmed

Summary

  • They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and Llama 3-70B in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in knowledge, where GLM-4.6V leads 37.4 to 20.8.

Side by side

GLM-4.6V and Llama 3-70B specifications
GLM-4.6VLlama 3-70B
ProviderZ.ai (Zhipu)Meta
Noometry Index40.928.5
Released2025-12-082024-04-18
WeightsOpenOpen
Context window128K—
Max output33K—
Input $ / M tokens$0.30—
Output $ / M tokens$0.90—
Results tracked1231

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.2 (#128), Llama 3-70B: 35.3 (#215)

Coding benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Coding13901206
BigCodeBench Instruct—43.6%
BigCodeBench Complete—54.5%
HumanEval+—72%
MBPP+—69%

Agentic & Tool Use Not comparable

GLM-4.6V: —, Llama 3-70B: 20.9 (#132)

Agentic & Tool Use benchmarks
BenchmarkGLM-4.6VLlama 3-70B
Cybench—5%

Reasoning GLM-4.6V leads

GLM-4.6V: 26.5 (#117), Llama 3-70B: 17.4 (#284)

Reasoning benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Hard Prompts13681195
Kagi LLM Benchmark—35.1%
DTBench—54.2%
Epoch Capabilities Index—122.91
ForecastBench—57.1
WinoGrande—83.5%

Math Not comparable

GLM-4.6V: —, Llama 3-70B: 12.0 (#299)

Math benchmarks
BenchmarkGLM-4.6VLlama 3-70B
OTIS Mock AIME 2024-2025—4.3%
LMArena Math—1218
MATH Level 5—22.6%

Knowledge GLM-4.6V leads

GLM-4.6V: 37.4 (#148), Llama 3-70B: 20.8 (#272)

Knowledge benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Expert13721149
GPQA Diamond—40.6%
MMLU—79.3%

Multimodal Not comparable

GLM-4.6V: 34.2 (#83), Llama 3-70B: —

Multimodal benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Vision1164—

Multilingual GLM-4.6V leads

GLM-4.6V: 48.8 (#135), Llama 3-70B: 33.8 (#246)

Multilingual benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Non-English13591142
LMArena Chinese14261114
LMArena Russian13411159
LMArena French—1231
LMArena German—1169
LMArena Japanese—1017
LMArena Korean—1017
LMArena Spanish—1241

Instruction Following GLM-4.6V leads

GLM-4.6V: 71.6 (#145), Llama 3-70B: 62.8 (#233)

Instruction Following benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Instruction Following13511194

Long Context GLM-4.6V leads

GLM-4.6V: 41.3 (#138), Llama 3-70B: 35.6 (#235)

Long Context benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Longer Query13581174

Writing & Preference GLM-4.6V leads

GLM-4.6V: 56.8 (#132), Llama 3-70B: 43.0 (#225)

Writing & Preference benchmarks
BenchmarkGLM-4.6VLlama 3-70B
LMArena Text13771221
LMArena Creative Writing13471210
LMArena Multi-Turn13591223

Frequently asked questions

Is GLM-4.6V better than Llama 3-70B?

GLM-4.6V is the stronger model overall, scoring 40.9 to 28.5 on the Noometry Index.

Is GLM-4.6V or Llama 3-70B better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 35.3 in the Noometry coding category.

How many benchmarks do GLM-4.6V and Llama 3-70B share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Llama 3-70B has 31.

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