Model comparison
GLM-4.5 vs Qwen1.5-32B
GLM-4.5 is the stronger model overall, scoring 41.4 to 30.0 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Qwen1.5-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5 leads 57.7 to 34.4.
Side by side
| GLM-4.5 | Qwen1.5-32B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 41.4 | 30.0 |
| Released | 2025-07-27 | 2024-02-04 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 21 |
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Category by category
Coding GLM-4.5 leads
GLM-4.5: 41.1 (#121), Qwen1.5-32B: 31.1 (#278)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Coding | 1434 | 1155 |
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| BigCodeBench Instruct | — | 32.3% |
| BigCodeBench Complete | — | 42% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Reasoning GLM-4.5 leads
GLM-4.5: 27.7 (#99), Qwen1.5-32B: 20.9 (#210)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Hard Prompts | 1430 | 1131 |
| Kagi LLM Benchmark | 57.9% | — |
Math GLM-4.5 leads
GLM-4.5: 36.3 (#119), Qwen1.5-32B: 30.5 (#207)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Math | 1427 | 1155 |
Knowledge GLM-4.5 leads
GLM-4.5: 35.5 (#172), Qwen1.5-32B: 13.5 (#291)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Expert | 1433 | 1126 |
| GPQA Diamond | — | 30.7% |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| MMLU | — | 74.4% |
Multilingual GLM-4.5 leads
GLM-4.5: 53.0 (#74), Qwen1.5-32B: 31.6 (#254)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Non-English | 1417 | 1106 |
| LMArena Chinese | 1465 | 1176 |
| LMArena French | 1423 | 1100 |
| LMArena German | 1406 | 1058 |
| LMArena Japanese | 1416 | 1027 |
| LMArena Korean | 1382 | 1007 |
| LMArena Russian | 1414 | 1073 |
| LMArena Spanish | 1454 | 1089 |
Instruction Following GLM-4.5 leads
GLM-4.5: 74.3 (#100), Qwen1.5-32B: 58.0 (#260)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Instruction Following | 1405 | 1116 |
Long Context GLM-4.5 leads
GLM-4.5: 38.2 (#196), Qwen1.5-32B: 34.7 (#241)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Longer Query | 1413 | 1146 |
| Fiction.LiveBench | 58.3% | — |
Writing & Preference GLM-4.5 leads
GLM-4.5: 57.7 (#121), Qwen1.5-32B: 34.4 (#266)
| Benchmark | GLM-4.5 | Qwen1.5-32B |
|---|---|---|
| LMArena Text | 1430 | 1137 |
| LMArena Creative Writing | 1395 | 1083 |
| LMArena Multi-Turn | 1415 | 1140 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
Frequently asked questions
Is GLM-4.5 better than Qwen1.5-32B?
GLM-4.5 is the stronger model overall, scoring 41.4 to 30.0 on the Noometry Index.
Is GLM-4.5 or Qwen1.5-32B better for coding?
GLM-4.5 scores higher on coding benchmarks: 41.1 versus 31.1 in the Noometry coding category.
How many benchmarks do GLM-4.5 and Qwen1.5-32B share?
17 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Qwen1.5-32B has 21.