Model comparison
GLM-4.6V vs Llama 2-7B
GLM-4.6V is the stronger model overall, scoring 40.9 to 28.6 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 2-7B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6V leads 56.8 to 28.1.
Side by side
| GLM-4.6V | Llama 2-7B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 40.9 | 28.6 |
| Released | 2025-12-08 | 2023-07-18 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 33K | — |
| Input $ / M tokens | $0.30 | — |
| Output $ / M tokens | $0.90 | — |
| Results tracked | 12 | 29 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.2 (#128), Llama 2-7B: 28.7 (#302)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Coding | 1390 | 1002 |
Reasoning GLM-4.6V leads
GLM-4.6V: 26.5 (#117), Llama 2-7B: 15.1 (#309)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1009 |
| Chess Puzzles | — | 0% |
| BIG-Bench Hard | — | 39.2% |
| Epoch Capabilities Index | — | 98.54 |
| HellaSwag | — | 77.2% |
| LAMBADA | — | 73.3% |
| PIQA | — | 78.8% |
| WinoGrande | — | 69.2% |
Math Not comparable
GLM-4.6V: —, Llama 2-7B: 28.2 (#231)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Math | — | 1042 |
| GSM8K | — | 16.7% |
Knowledge GLM-4.6V leads
GLM-4.6V: 37.4 (#148), Llama 2-7B: 27.7 (#243)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Expert | 1372 | 1036 |
| ARC (AI2) Challenge | — | 45.9% |
| BoolQ | — | 77.9% |
| MMLU | — | 45.8% |
| OpenBookQA | — | 58.6% |
| TriviaQA | — | 73.7% |
Multimodal Not comparable
GLM-4.6V: 34.2 (#83), Llama 2-7B: —
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Vision | 1164 | — |
| ScienceQA | — | 43.1% |
Multilingual GLM-4.6V leads
GLM-4.6V: 48.8 (#135), Llama 2-7B: 23.9 (#288)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Non-English | 1359 | 973 |
| LMArena Chinese | 1426 | 973 |
| LMArena Russian | 1341 | 995 |
| LMArena French | — | 969 |
| LMArena German | — | 978 |
| LMArena Spanish | — | 1007 |
Instruction Following GLM-4.6V leads
GLM-4.6V: 71.6 (#145), Llama 2-7B: 51.0 (#293)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Instruction Following | 1351 | 1006 |
Long Context GLM-4.6V leads
GLM-4.6V: 41.3 (#138), Llama 2-7B: 30.4 (#282)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Longer Query | 1358 | 999 |
Writing & Preference GLM-4.6V leads
GLM-4.6V: 56.8 (#132), Llama 2-7B: 28.1 (#293)
| Benchmark | GLM-4.6V | Llama 2-7B |
|---|---|---|
| LMArena Text | 1377 | 1053 |
| LMArena Creative Writing | 1347 | 1033 |
| LMArena Multi-Turn | 1359 | 1029 |
Frequently asked questions
Is GLM-4.6V better than Llama 2-7B?
GLM-4.6V is the stronger model overall, scoring 40.9 to 28.6 on the Noometry Index.
Is GLM-4.6V or Llama 2-7B better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.2 versus 28.7 in the Noometry coding category.
How many benchmarks do GLM-4.6V and Llama 2-7B share?
11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Llama 2-7B has 29.