Qwen3.7 Max vs Hy3
Updated October 21, 2026. 16 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Qwen3.7 Max and Hy3 are level for coding, 45.1 against 43.9 on the Vibe Coding Index, so price and context decide.
Pick Hy3 when output tokens cost 8.4x less. Pick Qwen3.7 Max when the context window is larger, 1M against 262K tokens, or when what matters is LMArena WebDev or SciCode, where it leads.
- Shared results
- 16
- Qwen3.7 Max only
- 43
- Hy3 only
- 28
- Like-for-like categories
- 4 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
No call
Level: 45.1 against 43.9, inside 2 points.
One benchmark behind each score
Intelligence
AA Intelligence Index
No call
Only Qwen3.7 Max has a AA Intelligence Index result, 29.5.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Max has a AA Agentic Index result, 22.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.7 Max has a GPQA Diamond result, 90.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.7 Max has a MMLU Pro result, 89.3%.
Directional only
Web design
Design Arena: websites
Qwen3.7 Max
Qwen3.7 Max leads, 1274 against 1230.
Same board, both measured
Long documents
Listed context window
Qwen3.7 Max
Qwen3.7 Max takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hy3
Qwen3.7 Max $0.0037, Hy3 $0.0004 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.7 Max has the number, $4.69.
Directional only
At a glance
- Coding index
- Qwen3.7 Max 45.1 from 1 benchmark, Hy3 43.9 from 1 benchmark.
- Widest category
- Web design, 6.7 points apart on average over 8 shared benchmarks.
- Widest single gap
- Design Arena: data viz: Qwen3.7 Max 1275 against Hy3 1163, 14.0 points apart on a 0 to 100 scale.
- Output price
- Qwen3.7 Max $4.425 against Hy3 $0.528 per million output tokens, 8.4x apart.
- Context window
- Qwen3.7 Max takes 1M tokens, Hy3 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Qwen3.7 Max | Bars | Hy3 | Ties |
|---|---|---|---|---|
| Coding | 5 | 0 | ||
| Reasoning | 2 | 0 | ||
| Web design | 8 | 0 | ||
| General | 0 | 0 | 1 tie | |
| All shared boards | 15 | 0 | 1 tie |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| LMArena WebDev | 1515 | 1507 | Qwen3.7 Max |
| AA Coding Index | 66.0 | Not measured | Only Qwen3.7 Max measured |
| LiveCodeBench (Vals AI) | 87.1% | Not measured | Only Qwen3.7 Max measured |
| SWE-bench Verified (Vals AI) | 68.8% | Not measured | Only Qwen3.7 Max measured |
| Vibe Code Bench (Vals AI) | 47.7% | Not measured | Only Qwen3.7 Max measured |
| Code migration (Vals AI) | 13.1% | Not measured | Only Qwen3.7 Max measured |
| Terminal-Bench 2.1 (Vals AI) | 61.0% | Not measured | Only Qwen3.7 Max measured |
| SciCode | 49.5% | 48.6% | Qwen3.7 Max |
| Terminal-Bench Hard (Artificial Analysis run) | 50.8% | Not measured | Only Qwen3.7 Max measured |
| ALE-Bench | 1189.4 | 838.6 | Qwen3.7 Max |
| LMArena Text: coding | Not measured | 1466 | Only Hy3 measured |
| LMArena Text: software and IT | Not measured | 1463 | Only Hy3 measured |
| LMArena WebDev: React | 1514 | 1511 | Qwen3.7 Max |
| LMArena WebDev: HTML | 1512 | 1487 | Qwen3.7 Max |
| Neither model has a result on the other 24 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.5 | Not measured | Only Qwen3.7 Max measured |
| Epoch Capabilities Index | 154.0 | Not measured | Only Qwen3.7 Max measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| AA Agentic Index | 22.5 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building web apps | 1208 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building full-stack apps | 1191 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building mobile apps | 1153 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | 1165 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building Godot games | 1187 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building games | 1161 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | 1158 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | 1196 | Not measured | Only Qwen3.7 Max measured |
| Finance Agent (Vals AI) | 47.8% | Not measured | Only Qwen3.7 Max measured |
| Tax Agent Bench (Vals AI) | 15.8% | Not measured | Only Qwen3.7 Max measured |
| Legal Research Bench (Vals AI) | 25.5% | Not measured | Only Qwen3.7 Max measured |
| Excel Modeling Benchmark (Vals AI) | 57.0% | Not measured | Only Qwen3.7 Max measured |
| τ²-Bench Telecom | 94.7% | Not measured | Only Qwen3.7 Max measured |
| Neither model has a result on the other 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| GPQA Diamond | 90.2% | Not measured | Only Qwen3.7 Max measured |
| GPQA Diamond (Artificial Analysis run) | 92.3% | 89.7% | Qwen3.7 Max |
| Humanity's Last Exam (Artificial Analysis run) | 40.5% | 33.5% | Qwen3.7 Max |
| GPQA Diamond (Epoch AI run) | 90.9% | Not measured | Only Qwen3.7 Max measured |
| SimpleBench | 70.4% | Not measured | Only Qwen3.7 Max measured |
| Chess puzzles | 26.0% | Not measured | Only Qwen3.7 Max measured |
| Mystery game puzzles | 32.0% | Not measured | Only Qwen3.7 Max measured |
| EBR-bench | 9.5% | Not measured | Only Qwen3.7 Max measured |
| LMArena Text: hard prompts | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: expert | Not measured | 1461 | Only Hy3 measured |
| LMArena Text: hard prompts in English | Not measured | 1455 | Only Hy3 measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | Not measured | Only Qwen3.7 Max measured |
| FrontierMath, tiers 1 to 3 | 64.6% | Not measured | Only Qwen3.7 Max measured |
| FrontierMath, tier 4 | 34.1% | Not measured | Only Qwen3.7 Max measured |
| ProofBench | 26.0% | Not measured | Only Qwen3.7 Max measured |
| LMArena Text: math | Not measured | 1473 | Only Hy3 measured |
| LMArena Text: mathematical work | Not measured | 1482 | Only Hy3 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| MMLU Pro | 89.3% | Not measured | Only Qwen3.7 Max measured |
| LegalBench (Vals AI) | 84.9% | Not measured | Only Qwen3.7 Max measured |
| CorpFin (Vals AI) | 63.7% | Not measured | Only Qwen3.7 Max measured |
| TaxEval (Vals AI) | 75.3% | Not measured | Only Qwen3.7 Max measured |
| MedCode (Vals AI) | 38.8% | Not measured | Only Qwen3.7 Max measured |
| SimpleQA Verified | 55.8% | Not measured | Only Qwen3.7 Max measured |
| LMArena Text: science | Not measured | 1457 | Only Hy3 measured |
| LMArena Text: medicine and healthcare | Not measured | 1452 | Only Hy3 measured |
| LMArena Text: legal and government | Not measured | 1422 | Only Hy3 measured |
| LMArena Text: business and finance | Not measured | 1424 | Only Hy3 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1274 | 1230 | Qwen3.7 Max |
| Design Arena: UI components | 1269 | 1205 | Qwen3.7 Max |
| Design Arena: game dev | 1265 | 1208 | Qwen3.7 Max |
| Design Arena: data viz | 1275 | 1163 | Qwen3.7 Max |
| Design Arena: 3D | 1266 | 1233 | Qwen3.7 Max |
| Design Arena: all code categories | 1275 | 1227 | Qwen3.7 Max |
| Design Arena: SVG | 1216 | 1199 | Qwen3.7 Max |
| Design Arena: ASCII art | 1211 | 1157 | Qwen3.7 Max |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index00
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 79.4% | Not measured | Only Qwen3.7 Max measured |
| IFBench | 80.5% | Not measured | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | 79.0% | 79.0% | Tie |
| DTBench | 92.3% | Not measured | Only Qwen3.7 Max measured |
| LMCA | 44.0% | Not measured | Only Qwen3.7 Max measured |
| LMArena Text | Not measured | 1438 | Only Hy3 measured |
| LMArena Text: instruction following | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: creative writing | Not measured | 1403 | Only Hy3 measured |
| LMArena Text: English | Not measured | 1448 | Only Hy3 measured |
| LMArena Text: non-English | Not measured | 1426 | Only Hy3 measured |
| LMArena Text: Chinese | Not measured | 1485 | Only Hy3 measured |
| LMArena Text: German | Not measured | 1449 | Only Hy3 measured |
| LMArena Text: Japanese | Not measured | 1397 | Only Hy3 measured |
| LMArena Text: Korean | Not measured | 1396 | Only Hy3 measured |
| LMArena Text: French | Not measured | 1456 | Only Hy3 measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Hy3 measured |
| LMArena Text: Russian | Not measured | 1432 | Only Hy3 measured |
| LMArena Text: Polish | Not measured | 1447 | Only Hy3 measured |
| LMArena Text: multi-turn | Not measured | 1436 | Only Hy3 measured |
| LMArena Text: longer queries | Not measured | 1442 | Only Hy3 measured |
| LMArena Text: writing and language | Not measured | 1414 | Only Hy3 measured |
| LMArena Text: entertainment and media | Not measured | 1400 | Only Hy3 measured |
| Neither model has a result on the other 24 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.7 Max | Hy3 | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Hy3 costs less
Repository review
50K input + 3K output tokens
Hy3 costs less
Agent loop
200K input + 10K output tokens
Hy3 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 | Qwen3.7 Max | Tencent Hy3 |
|---|---|---|
| Maker | Qwen | Tencent |
| Weights | No public weights listed | Open weights |
| Released | May 21, 2026 | July 6, 2026 |
| Context window | 1M | 262K |
| Input $/Mtok | $1.475 | $0.132 |
| Output $/Mtok | $4.425 | $0.528 |
| Coding index | 45.1 | 43.9 |
| Independent measurements behind it | 1 | 1 |
| Cost per solved task | $4.69 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.7 Max better than Hy3 for coding?
Qwen3.7 Max and Hy3 are level for coding, 45.1 against 43.9 on the Vibe Coding Index, so price and context decide. Pick Hy3 when output tokens cost 8.4x less. Pick Qwen3.7 Max when the context window is larger, 1M against 262K tokens, or when what matters is LMArena WebDev or SciCode, where it leads.
Which is cheaper, Qwen3.7 Max or Hy3?
Qwen3.7 Max costs $1.475 per million input tokens and $4.425 per million output tokens; Hy3 costs $0.132 and $0.528. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, Qwen3.7 Max or Hy3?
Qwen3.7 Max, with 1M tokens against 262K.
How many benchmarks is the Qwen3.7 Max vs Hy3 comparison based on?
16 benchmarks have a result for both models as of October 21, 2026. Qwen3.7 Max's coding index rests on 1 independent benchmark and Hy3's on 1. Where only one model has a result, the page says so instead of naming a winner.