Model comparison
GLM-4.5-Air vs Hy3
Hy3 is the stronger model overall, scoring 44.2 to 38.9 on the Noometry Index.
Last verified . 17 shared benchmarks.
TencentSummary
- They share 17 benchmarks with published results for both. GLM-4.5-Air scores higher in 0 categories and Hy3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where Hy3 leads 46.8 to 33.3.
- Hy3 is cheaper at $0.0825 / $0.33 per million input/output tokens, against $0.20 / $1.10 for GLM-4.5-Air.
- Hy3 accepts more context: 262K tokens versus 131K.
Side by side
| GLM-4.5-Air | Hy3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Tencent |
| Noometry Index | 38.9 | 44.2 |
| Released | 2025-07-20 | 2026-07-06 |
| Weights | Open | Open |
| Context window | 131K | 262K |
| Max output | 98K | 128K |
| Input $ / M tokens | $0.20 | $0.0825 |
| Output $ / M tokens | $1.10 | $0.33 |
| Results tracked | 27 | 19 |
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Category by category
Coding Hy3 leads
GLM-4.5-Air: 33.3 (#259), Hy3: 46.8 (#63)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Coding | 1397 | 1464 |
| LMArena WebDev | — | 1508 |
| GSO | 2.9% | — |
Reasoning Hy3 leads
GLM-4.5-Air: 24.1 (#166), Hy3: 26.1 (#136)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Hard Prompts | 1379 | 1447 |
| Kagi LLM Benchmark | 43% | — |
| NYT Connections (extended) | — | 41.2% |
| ForecastBench | 59.2 | — |
Math Hy3 leads
GLM-4.5-Air: 36.2 (#170), Hy3: 40.1 (#93)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Math | 1396 | 1475 |
| Omni-MATH | 39.1% | — |
Knowledge Hy3 leads
GLM-4.5-Air: 35.0 (#191), Hy3: 40.8 (#114)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Expert | 1370 | 1460 |
| Humanity's Last Exam | 8.1% | — |
| MMLU-Pro | 76.2% | — |
| Vectara Hallucination Rate | 9.3% | — |
| GPQA (HELM) | 59.4% | — |
Multilingual Hy3 leads
GLM-4.5-Air: 49.1 (#135), Hy3: 53.5 (#65)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Non-English | 1366 | 1426 |
| LMArena Chinese | 1426 | 1493 |
| LMArena French | 1399 | 1461 |
| LMArena German | 1377 | 1439 |
| LMArena Japanese | 1348 | 1392 |
| LMArena Korean | 1308 | 1395 |
| LMArena Russian | 1373 | 1432 |
| LMArena Spanish | 1386 | 1456 |
Instruction Following Hy3 leads
GLM-4.5-Air: 69.6 (#171), Hy3: 75.1 (#70)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Instruction Following | 1354 | 1426 |
| IFEval | 81.2% | — |
Long Context Hy3 leads
GLM-4.5-Air: 41.6 (#135), Hy3: 44.1 (#75)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Longer Query | 1366 | 1442 |
Writing & Preference Hy3 leads
GLM-4.5-Air: 55.9 (#139), Hy3: 62.2 (#81)
| Benchmark | GLM-4.5-Air | Hy3 |
|---|---|---|
| LMArena Text | 1384 | 1439 |
| LMArena Creative Writing | 1343 | 1402 |
| LMArena Multi-Turn | 1371 | 1436 |
| WildBench | 78.9% | — |
Frequently asked questions
Is GLM-4.5-Air better than Hy3?
Hy3 is the stronger model overall, scoring 44.2 to 38.9 on the Noometry Index.
Which is cheaper, GLM-4.5-Air or Hy3?
Hy3 is cheaper. It lists at $0.0825 per million input tokens and $0.33 per million output tokens; GLM-4.5-Air lists at $0.20 and $1.10.
Is GLM-4.5-Air or Hy3 better for coding?
Hy3 scores higher on coding benchmarks: 46.8 versus 33.3 in the Noometry coding category.
Which has the bigger context window?
Hy3 does, with 262K tokens against 131K.
How many benchmarks do GLM-4.5-Air and Hy3 share?
17 benchmarks have published results for both models. GLM-4.5-Air has 27 scored results on Noometry and Hy3 has 19.