Model comparison
GLM-4.5-Air vs Qwen3-30B-A3B
GLM-4.5-Air and Qwen3-30B-A3B score almost the same on the Noometry Index (38.9 vs 38.9), so choose on price, context window or the category you care about most.
Last verified . 18 shared benchmarks.
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. GLM-4.5-Air scores higher in 3 categories and Qwen3-30B-A3B in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in long context, where GLM-4.5-Air leads 41.6 to 31.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 43% for GLM-4.5-Air and 54.9% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
- GLM-4.5-Air accepts more context: 131K tokens versus 41K.
Side by side
| GLM-4.5-Air | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.9 | 38.9 |
| Released | 2025-07-20 | 2025-04-28 |
| Weights | Open | Open |
| Context window | 131K | 41K |
| Max output | 98K | 16K |
| Input $ / M tokens | $0.20 | $0.12 |
| Output $ / M tokens | $1.10 | $0.50 |
| Results tracked | 27 | 32 |
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Category by category
Coding Qwen3-30B-A3B leads
GLM-4.5-Air: 33.3 (#259), Qwen3-30B-A3B: 37.5 (#194)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Coding | 1397 | 1416 |
| SciCode | — | 33.3% |
| GSO | 2.9% | — |
| WeirdML | — | 29.8% |
Agentic & Tool Use Not comparable
GLM-4.5-Air: —, Qwen3-30B-A3B: 29.8 (#82)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning GLM-4.5-Air leads
GLM-4.5-Air: 24.1 (#166), Qwen3-30B-A3B: 22.2 (#204)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| Kagi LLM Benchmark | 43% | 54.9% |
| LMArena Hard Prompts | 1379 | 1398 |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 8% |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
| Epoch Capabilities Index | — | 139.63 |
| ForecastBench | 59.2 | — |
Math Qwen3-30B-A3B leads
GLM-4.5-Air: 36.2 (#170), Qwen3-30B-A3B: 37.4 (#157)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Math | 1396 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| OTIS Mock AIME 2024-2025 | — | 70.3% |
| Omni-MATH | 39.1% | — |
Knowledge Qwen3-30B-A3B leads
GLM-4.5-Air: 35.0 (#191), Qwen3-30B-A3B: 41.8 (#105)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Expert | 1370 | 1396 |
| GPQA Diamond | — | 70.1% |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Confabulations | — | 12.3% |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual Too close to call
GLM-4.5-Air: 49.1 (#135), Qwen3-30B-A3B: 49.5 (#132)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1366 | 1372 |
| LMArena Chinese | 1426 | 1433 |
| LMArena French | 1399 | 1418 |
| LMArena German | 1377 | 1380 |
| LMArena Japanese | 1348 | 1337 |
| LMArena Korean | 1308 | 1331 |
| LMArena Russian | 1373 | 1370 |
| LMArena Spanish | 1386 | 1404 |
Instruction Following Qwen3-30B-A3B leads
GLM-4.5-Air: 69.6 (#171), Qwen3-30B-A3B: 72.0 (#142)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1354 | 1363 |
| IFEval | 81.2% | — |
Long Context GLM-4.5-Air leads
GLM-4.5-Air: 41.6 (#135), Qwen3-30B-A3B: 31.0 (#283)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1366 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Too close to call
GLM-4.5-Air: 55.9 (#139), Qwen3-30B-A3B: 55.6 (#143)
| Benchmark | GLM-4.5-Air | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1384 | 1384 |
| LMArena Creative Writing | 1343 | 1317 |
| LMArena Multi-Turn | 1371 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than Qwen3-30B-A3B?
GLM-4.5-Air and Qwen3-30B-A3B score almost the same on the Noometry Index (38.9 vs 38.9), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.5-Air or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; GLM-4.5-Air lists at $0.20 and $1.10.
Is GLM-4.5-Air or Qwen3-30B-A3B better for coding?
Qwen3-30B-A3B scores higher on coding benchmarks: 37.5 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
GLM-4.5-Air does, with 131K tokens against 41K.
How many benchmarks do GLM-4.5-Air and Qwen3-30B-A3B share?
18 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Qwen3-30B-A3B has 32.