Model comparison
GLM-4.5-Air vs Qwen1.5 4b Chat
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 28.8 on the Noometry Index.
Last verified . 13 shared benchmarks.
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. GLM-4.5-Air scores higher in 8 categories and Qwen1.5 4b Chat in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5-Air leads 55.9 to 23.8.
Side by side
| GLM-4.5-Air | Qwen1.5 4b Chat | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.9 | 28.8 |
| Released | 2025-07-20 | — |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.20 | — |
| Output $ / M tokens | $1.10 | — |
| Results tracked | 27 | 13 |
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Category by category
Coding GLM-4.5-Air leads
GLM-4.5-Air: 33.3 (#259), Qwen1.5 4b Chat: 29.1 (#308)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Coding | 1397 | 999 |
| GSO | 2.9% | — |
Reasoning GLM-4.5-Air leads
GLM-4.5-Air: 24.1 (#166), Qwen1.5 4b Chat: 18.5 (#279)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Hard Prompts | 1379 | 976 |
| Kagi LLM Benchmark | 43% | — |
| ForecastBench | 59.2 | — |
Math GLM-4.5-Air leads
GLM-4.5-Air: 36.2 (#170), Qwen1.5 4b Chat: 30.4 (#234)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Math | 1396 | 1026 |
| Omni-MATH | 39.1% | — |
Knowledge GLM-4.5-Air leads
GLM-4.5-Air: 35.0 (#191), Qwen1.5 4b Chat: 26.7 (#255)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Expert | 1370 | 980 |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual GLM-4.5-Air leads
GLM-4.5-Air: 49.1 (#135), Qwen1.5 4b Chat: 24.1 (#290)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Non-English | 1366 | 979 |
| LMArena Chinese | 1426 | 1024 |
| LMArena German | 1377 | 902 |
| LMArena Russian | 1373 | 952 |
| LMArena French | 1399 | — |
| LMArena Japanese | 1348 | — |
| LMArena Korean | 1308 | — |
| LMArena Spanish | 1386 | — |
Instruction Following GLM-4.5-Air leads
GLM-4.5-Air: 69.6 (#171), Qwen1.5 4b Chat: 49.0 (#300)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Instruction Following | 1354 | 978 |
| IFEval | 81.2% | — |
Long Context GLM-4.5-Air leads
GLM-4.5-Air: 41.6 (#135), Qwen1.5 4b Chat: 30.1 (#290)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Longer Query | 1366 | 988 |
Writing & Preference GLM-4.5-Air leads
GLM-4.5-Air: 55.9 (#139), Qwen1.5 4b Chat: 23.8 (#309)
| Benchmark | GLM-4.5-Air | Qwen1.5 4b Chat |
|---|---|---|
| LMArena Text | 1384 | 997 |
| LMArena Creative Writing | 1343 | 969 |
| LMArena Multi-Turn | 1371 | 977 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than Qwen1.5 4b Chat?
GLM-4.5-Air is the stronger model overall, scoring 38.9 to 28.8 on the Noometry Index.
Is GLM-4.5-Air or Qwen1.5 4b Chat better for coding?
GLM-4.5-Air scores higher on coding benchmarks: 33.3 versus 29.1 in the Noometry coding category.
How many benchmarks do GLM-4.5-Air and Qwen1.5 4b Chat share?
13 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Qwen1.5 4b Chat has 13.