Model comparison
Hy3 vs Qwen2.5-VL 72B Instruct
Hy3 is the stronger model overall, scoring 43.6 to 29.4 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in reasoning, where Hy3 leads 25.0 to 20.0.
- Hy3 is cheaper at $0.13 / $0.53 per million input/output tokens, against $2.80 / $8.40 for Qwen2.5-VL 72B Instruct.
- Hy3 accepts more context: 262K tokens versus 131K.
Side by side
| Hy3 | Qwen2.5-VL 72B Instruct | |
|---|---|---|
| Provider | Tencent | Alibaba (Qwen) |
| Noometry Index | 43.6 | 29.4 |
| Released | 2026-07-06 | 2024-09 |
| Weights | Open | Open |
| Context window | 262K | 131K |
| Max output | 128K | 8K |
| Input $ / M tokens | $0.13 | $2.80 |
| Output $ / M tokens | $0.53 | $8.40 |
| Results tracked | 17 | 6 |
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Category by category
Coding Not comparable
Hy3: 46.6 (#60), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena WebDev | 1509 | — |
| LMArena Coding | 1465 | — |
Agentic & Tool Use Not comparable
Hy3: —, Qwen2.5-VL 72B Instruct: 18.4 (#136)
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| OSWorld | — | 5% |
Reasoning Hy3 leads
Hy3: 25.0 (#134), Qwen2.5-VL 72B Instruct: 20.0 (#228)
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| Kagi LLM Benchmark | — | 36% |
| NYT Connections (extended) | 41.2% | — |
| LMArena Hard Prompts | 1449 | — |
Math Not comparable
Hy3: 37.4 (#98), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Math | 1475 | — |
Knowledge Not comparable
Hy3: 40.2 (#108), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Expert | 1461 | — |
Multimodal Not comparable
Hy3: —, Qwen2.5-VL 72B Instruct: 32.9 (#92)
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Vision | — | 1107 |
| Video-MME | — | 73.5% |
| GeoBench | — | 62% |
| SpatialViz-Bench | — | 33.3% |
Multilingual Not comparable
Hy3: 53.7 (#60), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Non-English | 1427 | — |
| LMArena Chinese | 1496 | — |
| LMArena French | 1461 | — |
| LMArena Korean | 1390 | — |
| LMArena Russian | 1435 | — |
| LMArena Spanish | 1448 | — |
Instruction Following Not comparable
Hy3: 75.3 (#68), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Instruction Following | 1425 | — |
Long Context Not comparable
Hy3: 44.1 (#70), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Longer Query | 1443 | — |
Writing & Preference Not comparable
Hy3: 62.5 (#75), Qwen2.5-VL 72B Instruct: —
| Benchmark | Hy3 | Qwen2.5-VL 72B Instruct |
|---|---|---|
| LMArena Text | 1442 | — |
| LMArena Creative Writing | 1399 | — |
| LMArena Multi-Turn | 1436 | — |
Frequently asked questions
Is Hy3 better than Qwen2.5-VL 72B Instruct?
Hy3 is the stronger model overall, scoring 43.6 to 29.4 on the Noometry Index.
Which is cheaper, Hy3 or Qwen2.5-VL 72B Instruct?
Hy3 is cheaper. It lists at $0.13 per million input tokens and $0.53 per million output tokens; Qwen2.5-VL 72B Instruct lists at $2.80 and $8.40.
Which has the bigger context window?
Hy3 does, with 262K tokens against 131K.
How many benchmarks do Hy3 and Qwen2.5-VL 72B Instruct share?
0 benchmarks have published results for both models. Hy3 has 17 scored results on Noometry and Qwen2.5-VL 72B Instruct has 6.