Model comparison
GLM-4.5V vs Qwen1.5-72B
GLM-4.5V is the stronger model overall, scoring 39.8 to 30.8 on the Noometry Index.
Last verified . 13 shared benchmarks.
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. GLM-4.5V scores higher in 8 categories and Qwen1.5-72B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.5V leads 37.5 to 11.5.
Side by side
| GLM-4.5V | Qwen1.5-72B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 39.8 | 30.8 |
| Released | 2025-08-11 | 2024-02-04 |
| Weights | Open | Open |
| Context window | 64K | — |
| Max output | 16K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $1.80 | — |
| Results tracked | 15 | 22 |
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Category by category
Coding GLM-4.5V leads
GLM-4.5V: 39.5 (#155), Qwen1.5-72B: 31.9 (#277)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Coding | 1347 | 1165 |
| BigCodeBench Instruct | — | 33.2% |
| BigCodeBench Complete | — | 40.3% |
| HumanEval+ | — | 59.1% |
| MBPP+ | — | 61.6% |
Reasoning GLM-4.5V leads
GLM-4.5V: 27.4 (#119), Qwen1.5-72B: 22.2 (#203)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Hard Prompts | 1334 | 1148 |
| Kagi LLM Benchmark | 59.8% | — |
Math GLM-4.5V leads
GLM-4.5V: 37.4 (#159), Qwen1.5-72B: 33.2 (#205)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Math | 1354 | 1164 |
Knowledge GLM-4.5V leads
GLM-4.5V: 37.5 (#156), Qwen1.5-72B: 11.5 (#300)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Expert | 1353 | 1136 |
| GPQA Diamond | — | 28.8% |
Multimodal Not comparable
GLM-4.5V: 34.3 (#92), Qwen1.5-72B: —
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual GLM-4.5V leads
GLM-4.5V: 44.6 (#177), Qwen1.5-72B: 33.2 (#253)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Non-English | 1303 | 1135 |
| LMArena Chinese | 1337 | 1186 |
| LMArena Russian | 1298 | 1104 |
| LMArena Spanish | 1336 | 1110 |
| LMArena French | — | 1159 |
| LMArena German | — | 1084 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1050 |
Instruction Following GLM-4.5V leads
GLM-4.5V: 69.2 (#175), Qwen1.5-72B: 59.3 (#256)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Instruction Following | 1311 | 1141 |
Long Context GLM-4.5V leads
GLM-4.5V: 39.6 (#171), Qwen1.5-72B: 35.1 (#243)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Longer Query | 1304 | 1157 |
Writing & Preference GLM-4.5V leads
GLM-4.5V: 52.5 (#170), Qwen1.5-72B: 37.3 (#258)
| Benchmark | GLM-4.5V | Qwen1.5-72B |
|---|---|---|
| LMArena Text | 1333 | 1166 |
| LMArena Creative Writing | 1295 | 1137 |
| LMArena Multi-Turn | 1332 | 1160 |
Frequently asked questions
Is GLM-4.5V better than Qwen1.5-72B?
GLM-4.5V is the stronger model overall, scoring 39.8 to 30.8 on the Noometry Index.
Is GLM-4.5V or Qwen1.5-72B better for coding?
GLM-4.5V scores higher on coding benchmarks: 39.5 versus 31.9 in the Noometry coding category.
How many benchmarks do GLM-4.5V and Qwen1.5-72B share?
13 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Qwen1.5-72B has 22.