Qwen2.5 72B Instruct vs Hy4 preview
Qwen2.5 72B Instruct costs 5.6x less per output token than Hy4 preview ($0.40 vs $2.2509 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 26.5
- Output $/M
- $0.40
- Coding
- 44.3
- Overall
- No data
- Output $/M
- $2.2509
Qwen2.5 72B Instruct or Hy4 preview: which to pick
Only Hy4 preview has a coding score, 44.3 on the Vibe Coding Index; Qwen2.5 72B Instruct has none, so the two cannot be ranked on coding.
Pick Qwen2.5 72B Instruct for output tokens 5.6x cheaper ($0.40 vs $2.2509 per million).
No benchmark has tested both yet. Qwen2.5 72B Instruct has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and WeirdML; Hy4 preview on LMArena WebDev, Terminal-Bench 4 (Vals AI) and Vibe Code Bench (Vals AI). Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Hy4 preview has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen2.5 72B Instruct has a AA Intelligence Index result, 7.7.
Directional only
General
Vals Index
No call
Only Hy4 preview has a Vals Index result, 53.2%.
Directional only
Long documents
Listed context window
Hy4 preview
Hy4 preview takes 1.05M tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 72B Instruct
Qwen2.5 72B Instruct $0.0006, Hy4 preview $0.0019 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 72B Instruct not benchmarked, Hy4 preview 44.3 from 3 benchmarks.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Qwen2.5 72B Instruct $0.40 against Hy4 preview $2.2509 per million output tokens, 5.6x apart.
- Context window
- Qwen2.5 72B Instruct takes 33K tokens, Hy4 preview 1.05M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index15 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1631 | Only Hy4 preview measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 8.1% | Only Hy4 preview measured |
| Vibe Code Bench (Vals AI) | Not measured | 77.5% | Only Hy4 preview measured |
| Code migration (Vals AI) | Not measured | 47.4% | Only Hy4 preview measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Hy4 preview measured |
| IOI (Vals AI) | Not measured | 59.3% | Only Hy4 preview measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 55.1% | Only Hy4 preview measured |
| CyberBench (Vals AI) | Not measured | 65.4% | Only Hy4 preview measured |
| LiveCodeBench (Artificial Analysis run) | 27.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| Terminal-Bench Hard (Artificial Analysis run) | 4.5% | Not measured | Only Qwen2.5 72B Instruct measured |
| WeirdML | 16.0% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: coding | 1292 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: software and IT | 1292 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena WebDev: React | Not measured | 1653 | Only Hy4 preview measured |
| LMArena WebDev: HTML | Not measured | 1620 | Only Hy4 preview measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| AA Intelligence Index | 7.7 | Not measured | Only Qwen2.5 72B Instruct measured |
| Epoch Capabilities Index | 129.0 | Not measured | Only Qwen2.5 72B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| SREBench (Vals AI) | Not measured | 2.3% | Only Hy4 preview measured |
| Finance Agent (Vals AI) | Not measured | 55.1% | Only Hy4 preview measured |
| Tax Agent Bench (Vals AI) | Not measured | 32.6% | Only Hy4 preview measured |
| Legal Research Bench (Vals AI) | Not measured | 45.2% | Only Hy4 preview measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 8.8% | Only Hy4 preview measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 58.1% | Only Hy4 preview measured |
| BioMysteryBench (Vals AI) | Not measured | 69.3% | Only Hy4 preview measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 1.4% | Only Hy4 preview measured |
| τ²-Bench Telecom | 34.5% | Not measured | Only Qwen2.5 72B Instruct measured |
| METR time horizons | 35.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| BALROG | 16.2% | Not measured | Only Qwen2.5 72B Instruct measured |
| TheAgentCompany | 5.7% | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 49.1% | Not measured | Only Qwen2.5 72B Instruct measured |
| Humanity's Last Exam (Artificial Analysis run) | 3.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| GPQA Diamond (Epoch AI run) | 49.1% | Not measured | Only Qwen2.5 72B Instruct measured |
| BIG-Bench Hard | 79.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts | 1271 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: expert | 1245 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: hard prompts in English | 1279 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| AA Math Index | 14.0 | Not measured | Only Qwen2.5 72B Instruct measured |
| AIME 2025 (Artificial Analysis run) | 14.0% | Not measured | Only Qwen2.5 72B Instruct measured |
| OTIS Mock AIME | 8.1% | Not measured | Only Qwen2.5 72B Instruct measured |
| ProofBench | Not measured | 75.0% | Only Hy4 preview measured |
| MATH level 5 | 63.2% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: math | 1283 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: mathematical work | 1290 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | Not measured | 83.8% | Only Hy4 preview measured |
| MedCode (Vals AI) | Not measured | 43.3% | Only Hy4 preview measured |
| MMLU Pro (Artificial Analysis run) | 72.0% | Not measured | Only Qwen2.5 72B Instruct measured |
| MMLU | 85.3% | Not measured | Only Qwen2.5 72B Instruct measured |
| AI2 Reasoning Challenge | 94.5% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: science | 1275 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: medicine and healthcare | 1258 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: legal and government | 1288 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: business and finance | 1253 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 9 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index25 boards measured
| Benchmark | Qwen2.5 72B Instruct | Hy4 preview | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.2% | Only Hy4 preview measured |
| Public Benefits Bench (Vals AI) | Not measured | 68.6% | Only Hy4 preview measured |
| MedScribe (Vals AI) | Not measured | 83.6% | Only Hy4 preview measured |
| IFBench | 36.9% | Not measured | Only Qwen2.5 72B Instruct measured |
| DTBench | 62.9% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMCA | 13.4% | Not measured | Only Qwen2.5 72B Instruct measured |
| HellaSwag | 84.8% | Not measured | Only Qwen2.5 72B Instruct measured |
| WinoGrande | 82.3% | Not measured | Only Qwen2.5 72B Instruct measured |
| PIQA | 82.6% | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text | 1269 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: instruction following | 1254 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: creative writing | 1221 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: English | 1283 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: non-English | 1252 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Chinese | 1273 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: German | 1234 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Japanese | 1180 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Korean | 1188 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: French | 1280 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Spanish | 1255 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: Russian | 1264 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: multi-turn | 1272 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: longer queries | 1281 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: writing and language | 1247 | Not measured | Only Qwen2.5 72B Instruct measured |
| LMArena Text: entertainment and media | 1211 | Not measured | Only Qwen2.5 72B Instruct measured |
| Neither model has a result on the other 21 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Qwen2.5 72B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 72B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 72B Instruct costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Qwen2.5 72B Instruct | Tencent Hy4 preview |
|---|---|---|
| Maker | Qwen | Tencent |
| Weights | Open weights | Open weights |
| Released | September 19, 2024 | August 28, 2026 |
| Context window | 33K | 1.05M |
| Input $/Mtok | $0.36 | $0.7506 |
| Output $/Mtok | $0.40 | $2.2509 |
| Coding index | Not benchmarked | 44.3 |
| Independent measurements behind it | 0 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen2.5 72B Instruct better than Hy4 preview for coding?
Only Hy4 preview has a coding score, 44.3 on the Vibe Coding Index; Qwen2.5 72B Instruct has none, so the two cannot be ranked on coding. Pick Qwen2.5 72B Instruct for output tokens 5.6x cheaper ($0.40 vs $2.2509 per million).
Which is cheaper, Qwen2.5 72B Instruct or Hy4 preview?
Qwen2.5 72B Instruct costs $0.36 per million input tokens and $0.40 per million output tokens; Hy4 preview costs $0.7506 and $2.2509. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen2.5 72B Instruct or Hy4 preview?
Hy4 preview, with 1.05M tokens against 33K.
Has any benchmark tested both Qwen2.5 72B Instruct and Hy4 preview?
No benchmark has tested both yet. Qwen2.5 72B Instruct has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and WeirdML; Hy4 preview on LMArena WebDev, Terminal-Bench 4 (Vals AI) and Vibe Code Bench (Vals AI). Compare them on price and context instead. Data as of October 21, 2026.