Qwen3.7 Max vs Extract
Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- 54.1
- Overall
- 61.7
- Output $/M
- $4.425
- Coding
- No data
- Overall
- No data
- Output $/M
- No data
Qwen3.7 Max or Extract: which to pick
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; Extract has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Qwen3.7 Max has results on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI); Extract has none yet. 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 Qwen3.7 Max has a coding score, so no call is made.
One side not measured
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
No call
Only Qwen3.7 Max has a Design Arena: websites result, 1274.
Directional only
Long documents
Listed context window
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Extract
Qwen3.7 Max $0.0037, Extract $0.0000 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 54.1 from 3 benchmarks, Extract not benchmarked.
- 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
- Qwen3.7 Max $4.425 against Extract Free per million output tokens.
- Context window
- Both take 1M tokens.
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 Index12 boards measured
| Benchmark | Qwen3.7 Max | Extract | Leader |
|---|---|---|---|
| LMArena WebDev | 1515 | Not measured | Only Qwen3.7 Max measured |
| 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% | Not measured | Only Qwen3.7 Max measured |
| Terminal-Bench Hard (Artificial Analysis run) | 50.8% | Not measured | Only Qwen3.7 Max measured |
| ALE-Bench | 1189.4 | Not measured | Only Qwen3.7 Max measured |
| LMArena WebDev: React | 1514 | Not measured | Only Qwen3.7 Max measured |
| LMArena WebDev: HTML | 1512 | Not measured | Only Qwen3.7 Max measured |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen3.7 Max | Extract | 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 measured
| Benchmark | Qwen3.7 Max | Extract | 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 | 1155 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: agents building Android apps | 1159 | 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 | 1197 | 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 27 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen3.7 Max | Extract | Leader |
|---|---|---|---|
| GPQA Diamond | 90.2% | Not measured | Only Qwen3.7 Max measured |
| GPQA Diamond (Artificial Analysis run) | 92.3% | Not measured | Only Qwen3.7 Max measured |
| Humanity's Last Exam (Artificial Analysis run) | 40.5% | Not measured | Only Qwen3.7 Max measured |
| 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 |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Qwen3.7 Max | Extract | 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 |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Qwen3.7 Max | Extract | 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 |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Qwen3.7 Max | Extract | Leader |
|---|---|---|---|
| Design Arena: websites | 1274 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: UI components | 1270 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: game dev | 1265 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: data viz | 1275 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: 3D | 1266 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: all code categories | 1275 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: SVG | 1217 | Not measured | Only Qwen3.7 Max measured |
| Design Arena: ASCII art | 1211 | Not measured | Only Qwen3.7 Max measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Qwen3.7 Max | Extract | 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% | Not measured | Only Qwen3.7 Max measured |
| DTBench | 92.3% | Not measured | Only Qwen3.7 Max measured |
| LMCA | 44.0% | Not measured | Only Qwen3.7 Max measured |
| Neither model has a result on the other 41 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
Extract costs less
Repository review
50K input + 3K output tokens
Extract costs less
Agent loop
200K input + 10K output tokens
Extract 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 | ScaleDown Extract |
|---|---|---|
| Maker | Qwen | Scaledown |
| Weights | No public weights listed | No public weights listed |
| Released | May 21, 2026 | October 13, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $1.475 | $0.04 |
| Output $/Mtok | $4.425 | Free |
| Coding index | 54.1 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $4.69 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.7 Max better than Extract for coding?
Only Qwen3.7 Max has a coding score, 54.1 on the Vibe Coding Index; Extract has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Qwen3.7 Max or Extract?
Qwen3.7 Max costs $1.475 per million input tokens and $4.425 per million output tokens; Extract costs $0.04 and Free. Cost per solved task is known for Qwen3.7 Max only.
Which has the bigger context window, Qwen3.7 Max or Extract?
Neither: both take 1M tokens.
Has any benchmark tested both Qwen3.7 Max and Extract?
No benchmark has tested both yet. Qwen3.7 Max has results on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI); Extract has none yet. Compare them on price and context instead. Data as of October 21, 2026.