Model comparison
GLM-4.6V vs Llama 3-70B
GLM-4.6V is the stronger model overall, scoring 41.3 to 28.8 on the Noometry Index.
Last verified . 11 shared benchmarks.
MetaSummary
- 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 38.0 to 20.8.
Side by side
| GLM-4.6V | Llama 3-70B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 41.3 | 28.8 |
| Released | 2025-12-08 | 2024-04-18 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 33K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 12 | 31 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.9 (#128), Llama 3-70B: 35.8 (#218)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Coding | 1390 | 1206 |
| BigCodeBench Instruct | — | 43.6% |
| BigCodeBench Complete | — | 54.5% |
| HumanEval+ | — | 72% |
| MBPP+ | — | 69% |
Agentic & Tool Use Not comparable
GLM-4.6V: —, Llama 3-70B: 21.1 (#139)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| Cybench | — | 5% |
Reasoning GLM-4.6V leads
GLM-4.6V: 27.6 (#115), Llama 3-70B: 18.0 (#288)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1195 |
| Kagi LLM Benchmark | — | 35.1% |
| DTBench | — | 54.2% |
| Epoch Capabilities Index | — | 122.93 |
| ForecastBench | — | 57.1 |
| WinoGrande | — | 83.5% |
Math Not comparable
GLM-4.6V: —, Llama 3-70B: 12.8 (#305)
| Benchmark | GLM-4.6V | Llama 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: 38.0 (#149), Llama 3-70B: 20.8 (#277)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Expert | 1371 | 1149 |
| GPQA Diamond | — | 40.6% |
| MMLU | — | 79.3% |
Multimodal Not comparable
GLM-4.6V: 34.8 (#90), Llama 3-70B: —
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual GLM-4.6V leads
GLM-4.6V: 48.6 (#141), Llama 3-70B: 33.6 (#251)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Non-English | 1359 | 1142 |
| LMArena Chinese | 1425 | 1114 |
| LMArena Russian | 1340 | 1159 |
| LMArena French | — | 1232 |
| LMArena German | — | 1169 |
| LMArena Japanese | — | 1017 |
| LMArena Korean | — | 1017 |
| LMArena Spanish | — | 1241 |
Instruction Following GLM-4.6V leads
GLM-4.6V: 71.4 (#151), Llama 3-70B: 62.5 (#238)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Instruction Following | 1352 | 1194 |
Long Context GLM-4.6V leads
GLM-4.6V: 41.3 (#143), Llama 3-70B: 35.6 (#240)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Longer Query | 1358 | 1174 |
Writing & Preference GLM-4.6V leads
GLM-4.6V: 56.6 (#137), Llama 3-70B: 42.8 (#231)
| Benchmark | GLM-4.6V | Llama 3-70B |
|---|---|---|
| LMArena Text | 1377 | 1221 |
| LMArena Creative Writing | 1347 | 1210 |
| LMArena Multi-Turn | 1360 | 1223 |
Frequently asked questions
Is GLM-4.6V better than Llama 3-70B?
GLM-4.6V is the stronger model overall, scoring 41.3 to 28.8 on the Noometry Index.
Is GLM-4.6V or Llama 3-70B better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.9 versus 35.8 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.