Qwen3.7 Max vs Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads Qwen3.7 Max on coding, 62.4 to 54.1 on the Vibe Coding Index, and Qwen3.7 Max costs 1.4x less per output token ($4.425 vs $6.00 per million). Updated October 22, 2026; 50 benchmarks have a result for both.
Qwen3.7 Max or Qwen3.8 Max (0902): which to pick
Pick Qwen3.8 Max (0902) for coding: it scores 62.4 on the Vibe Coding Index against 54.1 for Qwen3.7 Max.
Pick Qwen3.7 Max for output tokens 1.4x cheaper ($4.425 vs $6.00 per million) and work measured by MMLU Pro or LegalBench (Vals AI), where it leads.
- Shared results
- 50
- Qwen3.7 Max only
- 9
- Qwen3.8 Max (0902) only
- 63
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) scores 62.4 against 54.1.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 45.4 against 29.5.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 56.0 against 22.5.
Same board, both measured
Reasoning
GPQA Diamond
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 93.7% against 90.2%.
Same board, both measured
Knowledge
MMLU Pro
Qwen3.7 Max
Qwen3.7 Max leads, 89.3% against 88.6%.
Same board, both measured
Web design
Design Arena: websites
Qwen3.8 Max (0902)
Qwen3.8 Max (0902) leads, 1275 against 1274.
Same board, both measured
Long documents
Listed context window
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Max
Qwen3.7 Max $0.0037, Qwen3.8 Max (0902) $0.0050 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Qwen3.8 Max (0902)
Qwen3.7 Max $4.69, Qwen3.8 Max (0902) $1.32.
Published attempt cost and pass rate
At a glance
- Coding index
- Qwen3.7 Max 54.1 from 3 benchmarks, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
- Widest category
- Math, 14.7 points apart on average over 4 shared benchmarks.
- Widest single gap
- AA Agentic Index: Qwen3.7 Max 22.5 against Qwen3.8 Max (0902) 56.0, 33.5 points apart on a 0 to 100 scale.
- Output price
- Qwen3.7 Max $4.425 against Qwen3.8 Max (0902) $6.00 per million output tokens, 1.4x apart.
- Context window
- Both take 1M tokens.
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 | Qwen3.8 Max (0902) | Ties |
|---|---|---|---|---|
| Coding | 0 | 10 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 0 | 11 | ||
| Reasoning | 0 | 6 | ||
| Math | 0 | 4 | ||
| Knowledge | 3 | 3 | ||
| Web design | 1 | 6 | ||
| General | 1 | 3 | ||
| All shared boards | 5 | 45 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index010
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.3% | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev | 1515 | 1674 | Qwen3.8 Max (0902) |
| AA Coding Index | 66.0 | 76.2 | Qwen3.8 Max (0902) |
| LiveCodeBench (Vals AI) | 87.1% | 87.8% | Qwen3.8 Max (0902) |
| SWE-bench Verified (Vals AI) | 68.8% | 85.6% | Qwen3.8 Max (0902) |
| Terminal-Bench 4 (Vals AI) | Not measured | 34.3% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench (Vals AI) | 47.7% | 64.7% | Qwen3.8 Max (0902) |
| Code migration (Vals AI) | 13.1% | 24.0% | Qwen3.8 Max (0902) |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Qwen3.8 Max (0902) measured |
| IOI (Vals AI) | Not measured | 68.9% | Only Qwen3.8 Max (0902) measured |
| Terminal-Bench 2.1 (Vals AI) | 61.0% | 67.4% | Qwen3.8 Max (0902) |
| SWE-bench Multimodal (Vals AI) | Not measured | 42.5% | Only Qwen3.8 Max (0902) measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 12.8% | Only Qwen3.8 Max (0902) measured |
| SkillsBench (Vals AI) | Not measured | 42.0% | Only Qwen3.8 Max (0902) measured |
| CyberBench (Vals AI) | Not measured | 28.6% | Only Qwen3.8 Max (0902) measured |
| SciCode | 49.5% | 53.2% | Qwen3.8 Max (0902) |
| Terminal-Bench Hard (Artificial Analysis run) | 50.8% | Not measured | Only Qwen3.7 Max measured |
| FrontierSWE | Not measured | 17.8% | Only Qwen3.8 Max (0902) measured |
| ALE-Bench | 1189.4 | Not measured | Only Qwen3.7 Max measured |
| LMArena Text: coding | Not measured | 1502 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: software and IT | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena WebDev: React | 1514 | 1692 | Qwen3.8 Max (0902) |
| LMArena WebDev: HTML | 1512 | 1649 | Qwen3.8 Max (0902) |
| LMArena WebDev: from an image | Not measured | 1637 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Intelligence Index | 29.5 | 45.4 | Qwen3.8 Max (0902) |
| Epoch Capabilities Index | 154.0 | 157.4 | Qwen3.8 Max (0902) |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index011
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| AA Agentic Index | 22.5 | 56.0 | Qwen3.8 Max (0902) |
| Design Arena: agents building web apps | 1208 | 1300 | Qwen3.8 Max (0902) |
| Design Arena: agents building full-stack apps | 1191 | 1305 | Qwen3.8 Max (0902) |
| Design Arena: agents building mobile apps | 1155 | 1224 | Qwen3.8 Max (0902) |
| Design Arena: agents building Android apps | 1159 | 1196 | Qwen3.8 Max (0902) |
| Design Arena: agents building Godot games | 1187 | 1234 | Qwen3.8 Max (0902) |
| Design Arena: agents building games | 1161 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: HTML slides | 1108 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: PowerPoint slides | 1171 | 1233 | Qwen3.8 Max (0902) |
| Design Arena: spreadsheets | Not measured | 967 | Only Qwen3.8 Max (0902) measured |
| LiveBench research | Not measured | 69.9% | Only Qwen3.8 Max (0902) measured |
| LiveBench browser | Not measured | 32.0% | Only Qwen3.8 Max (0902) measured |
| LiveBench long agentic | Not measured | 42.3% | Only Qwen3.8 Max (0902) measured |
| Finance Agent (Vals AI) | 47.8% | 50.6% | Qwen3.8 Max (0902) |
| Tax Agent Bench (Vals AI) | 15.8% | 32.1% | Qwen3.8 Max (0902) |
| Legal Research Bench (Vals AI) | 25.5% | 47.6% | Qwen3.8 Max (0902) |
| Excel Modeling Benchmark (Vals AI) | 57.0% | 60.1% | Qwen3.8 Max (0902) |
| Terminal-Bench-Science (Vals AI) | Not measured | 12.9% | Only Qwen3.8 Max (0902) measured |
| τ²-Bench Telecom | 94.7% | Not measured | Only Qwen3.7 Max measured |
| APEX-Agents | Not measured | 63.3% | Only Qwen3.8 Max (0902) measured |
| LMArena Search | Not measured | 1261 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| GPQA Diamond | 90.2% | 93.7% | Qwen3.8 Max (0902) |
| LiveBench reasoning | Not measured | 88.2% | Only Qwen3.8 Max (0902) measured |
| MysteryMechanism (Vals AI) | Not measured | 23.9% | Only Qwen3.8 Max (0902) measured |
| MMMU Pro (Vals AI) | Not measured | 88.0% | Only Qwen3.8 Max (0902) measured |
| GPQA Diamond (Artificial Analysis run) | 92.3% | 92.8% | Qwen3.8 Max (0902) |
| Humanity's Last Exam (Artificial Analysis run) | 40.5% | 43.1% | Qwen3.8 Max (0902) |
| GPQA Diamond (Epoch AI run) | 90.9% | 92.7% | Qwen3.8 Max (0902) |
| SimpleBench | 70.4% | Not measured | Only Qwen3.7 Max measured |
| Chess puzzles | 26.0% | 46.0% | Qwen3.8 Max (0902) |
| Mystery game puzzles | 32.0% | 38.0% | Qwen3.8 Max (0902) |
| EBR-bench | 9.5% | Not measured | Only Qwen3.7 Max measured |
| LMArena Text: hard prompts | Not measured | 1496 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: expert | Not measured | 1507 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: hard prompts in English | Not measured | 1503 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: diagrams | Not measured | 1323 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: homework | Not measured | 1336 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | 100.0% | Qwen3.8 Max (0902) |
| FrontierMath, tiers 1 to 3 | 64.6% | 74.7% | Qwen3.8 Max (0902) |
| FrontierMath, tier 4 | 34.1% | 46.3% | Qwen3.8 Max (0902) |
| ProofBench | 26.0% | 58.0% | Qwen3.8 Max (0902) |
| LMArena Text: math | Not measured | 1501 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: mathematical work | Not measured | 1491 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| MMLU Pro | 89.3% | 88.6% | Qwen3.7 Max |
| LegalBench (Vals AI) | 84.9% | 83.6% | Qwen3.7 Max |
| CorpFin (Vals AI) | 63.7% | 65.8% | Qwen3.8 Max (0902) |
| TaxEval (Vals AI) | 75.3% | 75.5% | Qwen3.8 Max (0902) |
| MortgageTax (Vals AI) | Not measured | 64.0% | Only Qwen3.8 Max (0902) measured |
| MedCode (Vals AI) | 38.8% | 40.7% | Qwen3.8 Max (0902) |
| SimpleQA Verified | 55.8% | 47.3% | Qwen3.7 Max |
| LMArena Text: science | Not measured | 1512 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: medicine and healthcare | Not measured | 1503 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: legal and government | Not measured | 1492 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: business and finance | Not measured | 1480 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| Design Arena: websites | 1274 | 1275 | Qwen3.8 Max (0902) |
| Design Arena: UI components | 1267 | 1338 | Qwen3.8 Max (0902) |
| Design Arena: game dev | 1264 | 1312 | Qwen3.8 Max (0902) |
| Design Arena: data viz | 1275 | 1281 | Qwen3.8 Max (0902) |
| Design Arena: 3D | 1265 | 1336 | Qwen3.8 Max (0902) |
| Design Arena: all code categories | 1275 | 1293 | Qwen3.8 Max (0902) |
| Design Arena: SVG | 1216 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: ASCII art | 1211 | 1200 | Qwen3.7 Max |
| LiveBench design | Not measured | 78.6% | Only Qwen3.8 Max (0902) measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 78.4% | Only Qwen3.8 Max (0902) measured |
| Public Benefits Bench (Vals AI) | Not measured | 67.1% | Only Qwen3.8 Max (0902) measured |
| SAGE (Vals AI) | Not measured | 51.2% | Only Qwen3.8 Max (0902) measured |
| MedScribe (Vals AI) | 79.4% | 85.0% | Qwen3.8 Max (0902) |
| Vals Multimodal Index | Not measured | 65.4% | Only Qwen3.8 Max (0902) measured |
| IFBench | 80.5% | Not measured | Only Qwen3.7 Max measured |
| Long context reasoning (AA-LCR) | 79.0% | 80.3% | Qwen3.8 Max (0902) |
| DTBench | 92.3% | 92.0% | Qwen3.7 Max |
| LMCA | 44.0% | 46.2% | Qwen3.8 Max (0902) |
| Furniture assembly | Not measured | 20.0% | Only Qwen3.8 Max (0902) measured |
| LMArena Text | Not measured | 1483 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: instruction following | Not measured | 1481 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: creative writing | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision | Not measured | 1313 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: English | Not measured | 1491 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: non-English | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Chinese | Not measured | 1539 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: German | Not measured | 1478 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Japanese | Not measured | 1473 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Korean | Not measured | 1460 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: French | Not measured | 1498 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Spanish | Not measured | 1489 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Russian | Not measured | 1482 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: Polish | Not measured | 1471 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: multi-turn | Not measured | 1489 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: longer queries | Not measured | 1488 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: writing and language | Not measured | 1477 | Only Qwen3.8 Max (0902) measured |
| LMArena Text: entertainment and media | Not measured | 1464 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: English | Not measured | 1311 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: Chinese | Not measured | 1358 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: humor | Not measured | 1304 | Only Qwen3.8 Max (0902) measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Qwen3.8 Max (0902) measured |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.7 Max | Qwen3.8 Max (0902) | 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
Qwen3.7 Max costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Max costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Max 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 | Qwen3.8 Max (0902) |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | May 21, 2026 | September 3, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $1.475 | $2.00 |
| Output $/Mtok | $4.425 | $6.00 |
| Coding index | 54.1 | 62.4 |
| Independent measurements behind it | 3 | 5 |
| Cost per solved task | $4.69 | $1.32 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.7 Max better than Qwen3.8 Max (0902) for coding?
Pick Qwen3.8 Max (0902) for coding: it scores 62.4 on the Vibe Coding Index against 54.1 for Qwen3.7 Max. Pick Qwen3.7 Max for output tokens 1.4x cheaper ($4.425 vs $6.00 per million) and work measured by MMLU Pro or LegalBench (Vals AI), where it leads.
Which is cheaper, Qwen3.7 Max or Qwen3.8 Max (0902)?
Qwen3.7 Max costs $1.475 per million input tokens and $4.425 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Per solved SWE-bench Verified task, Qwen3.7 Max costs $4.69 and Qwen3.8 Max (0902) $1.32.
Which has the bigger context window, Qwen3.7 Max or Qwen3.8 Max (0902)?
Neither: both take 1M tokens.
How many benchmarks is the Qwen3.7 Max vs Qwen3.8 Max (0902) comparison based on?
50 benchmarks have a result for both models as of October 22, 2026. Qwen3.7 Max's coding index rests on 3 independent benchmarks and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.