Model comparison
GLM-4.5-Air vs Qwen3-Coder 480B-A35B Instruct
GLM-4.5-Air and Qwen3-Coder 480B-A35B Instruct score almost the same on the Noometry Index (38.9 vs 38.1), so choose on price, context window or the category you care about most.
Last verified . 19 shared benchmarks.
Alibaba (Qwen)Summary
- They share 19 benchmarks with published results for both. GLM-4.5-Air scores higher in 2 categories and Qwen3-Coder 480B-A35B Instruct in 6 categories; 6 gaps are clear of the uncertainty.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 43% for GLM-4.5-Air and 49.5% for Qwen3-Coder 480B-A35B Instruct.
- GLM-4.5-Air is cheaper at $0.20 / $1.10 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 131K.
Side by side
| GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.9 | 38.1 |
| Released | 2025-07-20 | 2025-04 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 98K | 66K |
| Input $ / M tokens | $0.20 | $1.50 |
| Output $ / M tokens | $1.10 | $7.50 |
| Results tracked | 27 | 25 |
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Category by category
Coding Qwen3-Coder 480B-A35B Instruct leads
GLM-4.5-Air: 33.3 (#259), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| GSO | 2.9% | 4.9% |
| LMArena Coding | 1397 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
GLM-4.5-Air: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning Qwen3-Coder 480B-A35B Instruct leads
GLM-4.5-Air: 24.1 (#166), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 43% | 49.5% |
| LMArena Hard Prompts | 1379 | 1372 |
| ForecastBench | 59.2 | — |
Math Qwen3-Coder 480B-A35B Instruct leads
GLM-4.5-Air: 36.2 (#170), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1396 | 1365 |
| Omni-MATH | 39.1% | — |
Knowledge Qwen3-Coder 480B-A35B Instruct leads
GLM-4.5-Air: 35.0 (#191), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1370 | 1338 |
| 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), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1366 | 1346 |
| LMArena Chinese | 1426 | 1357 |
| LMArena French | 1399 | 1398 |
| LMArena German | 1377 | 1325 |
| LMArena Japanese | 1348 | 1310 |
| LMArena Korean | 1308 | 1305 |
| LMArena Russian | 1373 | 1366 |
| LMArena Spanish | 1386 | 1360 |
Instruction Following Qwen3-Coder 480B-A35B Instruct leads
GLM-4.5-Air: 69.6 (#171), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1354 | 1355 |
| IFEval | 81.2% | — |
Long Context Too close to call
GLM-4.5-Air: 41.6 (#135), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1366 | 1378 |
Writing & Preference Too close to call
GLM-4.5-Air: 55.9 (#139), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | GLM-4.5-Air | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1384 | 1357 |
| LMArena Creative Writing | 1343 | 1333 |
| LMArena Multi-Turn | 1371 | 1365 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than Qwen3-Coder 480B-A35B Instruct?
GLM-4.5-Air and Qwen3-Coder 480B-A35B Instruct score almost the same on the Noometry Index (38.9 vs 38.1), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.5-Air or Qwen3-Coder 480B-A35B Instruct?
GLM-4.5-Air is cheaper. It lists at $0.20 per million input tokens and $1.10 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is GLM-4.5-Air or Qwen3-Coder 480B-A35B Instruct better for coding?
Qwen3-Coder 480B-A35B Instruct scores higher on coding benchmarks: 35.5 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 131K.
How many benchmarks do GLM-4.5-Air and Qwen3-Coder 480B-A35B Instruct share?
19 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.