Qwen3.5 Plus 2026-04-20 vs Qwen3.7 Plus
Qwen3.5 Plus 2026-04-20 leads Qwen3.7 Plus on coding, 39.5 to 33.2 on the Vibe Coding Index, and Qwen3.7 Plus costs 1.4x less per output token ($1.28 vs $1.80 per million). Updated October 22, 2026; 9 benchmarks have a result for both.
Qwen3.5 Plus 2026-04-20 or Qwen3.7 Plus: which to pick
Pick Qwen3.5 Plus 2026-04-20 for coding: it scores 39.5 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.
Pick Qwen3.7 Plus for output tokens 1.4x cheaper ($1.28 vs $1.80 per million) and work measured by Vibe Code Bench (Vals AI) or Epoch Capabilities Index, where it leads.
- Shared results
- 9
- Qwen3.5 Plus 2026-04-20 only
- 16
- Qwen3.7 Plus only
- 66
- Like-for-like categories
- 6 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
Qwen3.5 Plus 2026-04-20
Qwen3.5 Plus 2026-04-20 scores 39.5 against 33.2.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only Qwen3.7 Plus has a AA Intelligence Index result, 25.2.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.7 Plus has a AA Agentic Index result, 17.5.
Directional only
Reasoning
GPQA Diamond
No call
Only Qwen3.5 Plus 2026-04-20 has a GPQA Diamond result, 87.4%.
Directional only
Math
AIME
No call
Only Qwen3.5 Plus 2026-04-20 has a AIME result, 86.0%.
Directional only
Knowledge
MMLU Pro
No call
Only Qwen3.5 Plus 2026-04-20 has a MMLU Pro result, 87.2%.
Directional only
Web design
Design Arena: websites
No call
Only Qwen3.7 Plus has a Design Arena: websites result, 1269.
Directional only
Long documents
Listed context window
No call
Both take 1M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Plus
Qwen3.5 Plus 2026-04-20 $0.0012, Qwen3.7 Plus $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.5 Plus 2026-04-20 has the number, $1.35.
Directional only
At a glance
- Coding index
- Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- Coding, 30.6 points apart on average over 1 shared benchmark.
- Widest single gap
- Vibe Code Bench (Vals AI): Qwen3.5 Plus 2026-04-20 15.7% against Qwen3.7 Plus 46.4%, 30.6 points apart on a 0 to 100 scale.
- Output price
- Qwen3.5 Plus 2026-04-20 $1.80 against Qwen3.7 Plus $1.28 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 | Qwen3.5 Plus 2026-04-20 | Bars | Qwen3.7 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Intelligence | 0 | 1 | ||
| Reasoning | 0 | 1 | 1 tie | |
| Math | 0 | 1 | ||
| Knowledge | 0 | 1 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 8 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 55.9 | Only Qwen3.7 Plus measured |
| LiveCodeBench (Vals AI) | 85.3% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| SWE-bench Verified (Vals AI) | 71.2% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| Vibe Code Bench (Vals AI) | 15.7% | 46.4% | Qwen3.7 Plus |
| Code migration (Vals AI) | Not measured | 12.9% | Only Qwen3.7 Plus measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 52.8% | Only Qwen3.7 Plus measured |
| SkillsBench (Vals AI) | Not measured | 54.3% | Only Qwen3.7 Plus measured |
| SciCode | Not measured | 46.1% | Only Qwen3.7 Plus measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 47.0% | Only Qwen3.7 Plus measured |
| FrontierCode | Not measured | 10.2% | Only Qwen3.7 Plus measured |
| ALE-Bench | 608.9 | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text: coding | Not measured | 1473 | Only Qwen3.7 Plus measured |
| LMArena Text: software and IT | Not measured | 1473 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 25.2 | Only Qwen3.7 Plus measured |
| Epoch Capabilities Index | 146.2 | 147.0 | Qwen3.7 Plus |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 17.5 | Only Qwen3.7 Plus measured |
| Finance Agent (Vals AI) | Not measured | 38.2% | Only Qwen3.7 Plus measured |
| Tax Agent Bench (Vals AI) | Not measured | 10.5% | Only Qwen3.7 Plus measured |
| Legal Research Bench (Vals AI) | Not measured | 16.4% | Only Qwen3.7 Plus measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 49.3% | Only Qwen3.7 Plus measured |
| τ²-Bench Telecom | Not measured | 93.0% | Only Qwen3.7 Plus measured |
| OSWorld 2.0 | Not measured | 2.8% | Only Qwen3.7 Plus measured |
| Vending-Bench 2 | $1 | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| GPQA Diamond | 87.4% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| MMMU Pro (Vals AI) | 22.8% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 90.0% | Only Qwen3.7 Plus measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 35.6% | Only Qwen3.7 Plus measured |
| GPQA Diamond (Epoch AI run) | 84.8% | 87.9% | Qwen3.7 Plus |
| Chess puzzles | 8.0% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| Mystery game puzzles | 17.0% | 17.0% | Tie |
| LMArena Text: hard prompts | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Text: expert | Not measured | 1466 | Only Qwen3.7 Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1460 | Only Qwen3.7 Plus measured |
| LMArena Vision: diagrams | Not measured | 1292 | Only Qwen3.7 Plus measured |
| LMArena Vision: homework | Not measured | 1295 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 11 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AIME | 86.0% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| OTIS Mock AIME | 86.7% | 93.3% | Qwen3.7 Plus |
| FrontierMath, tiers 1 to 3 | Not measured | 34.4% | Only Qwen3.7 Plus measured |
| LMArena Text: math | Not measured | 1467 | Only Qwen3.7 Plus measured |
| LMArena Text: mathematical work | Not measured | 1470 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| MMLU Pro | 87.2% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| LegalBench (Vals AI) | 85.1% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| CaseLaw (Vals AI) | 59.7% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| CorpFin (Vals AI) | 65.3% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| MortgageTax (Vals AI) | 60.8% | 66.2% | Qwen3.7 Plus |
| MedQA (Vals AI) | 95.2% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| SimpleQA Verified | 25.4% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text: science | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1464 | Only Qwen3.7 Plus measured |
| LMArena Text: legal and government | Not measured | 1451 | Only Qwen3.7 Plus measured |
| LMArena Text: business and finance | Not measured | 1435 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 9 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1269 | Only Qwen3.7 Plus measured |
| Design Arena: UI components | Not measured | 1258 | Only Qwen3.7 Plus measured |
| Design Arena: game dev | Not measured | 1262 | Only Qwen3.7 Plus measured |
| Design Arena: data viz | Not measured | 1277 | Only Qwen3.7 Plus measured |
| Design Arena: 3D | Not measured | 1238 | Only Qwen3.7 Plus measured |
| Design Arena: all code categories | Not measured | 1268 | Only Qwen3.7 Plus measured |
| Design Arena: SVG | Not measured | 1207 | Only Qwen3.7 Plus measured |
| Design Arena: ASCII art | Not measured | 1143 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 30.4% | 39.3% | Qwen3.7 Plus |
| Vals Multimodal Index | Not measured | 53.9% | Only Qwen3.7 Plus measured |
| IFBench | Not measured | 78.0% | Only Qwen3.7 Plus measured |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only Qwen3.7 Plus measured |
| DTBench | 80.5% | 84.0% | Qwen3.7 Plus |
| LMCA | 36.4% | 37.6% | Qwen3.7 Plus |
| CL-bench | 19.8% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| CL-bench Life | 12.4% | Not measured | Only Qwen3.5 Plus 2026-04-20 measured |
| LMArena Text | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: instruction following | Not measured | 1439 | Only Qwen3.7 Plus measured |
| LMArena Text: creative writing | Not measured | 1438 | Only Qwen3.7 Plus measured |
| LMArena Vision | Not measured | 1278 | Only Qwen3.7 Plus measured |
| LMArena Text: English | Not measured | 1458 | Only Qwen3.7 Plus measured |
| LMArena Text: non-English | Not measured | 1445 | Only Qwen3.7 Plus measured |
| LMArena Text: Chinese | Not measured | 1509 | Only Qwen3.7 Plus measured |
| LMArena Text: German | Not measured | 1471 | Only Qwen3.7 Plus measured |
| LMArena Text: Japanese | Not measured | 1412 | Only Qwen3.7 Plus measured |
| LMArena Text: Korean | Not measured | 1413 | Only Qwen3.7 Plus measured |
| LMArena Text: French | Not measured | 1472 | Only Qwen3.7 Plus measured |
| LMArena Text: Spanish | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Russian | Not measured | 1457 | Only Qwen3.7 Plus measured |
| LMArena Text: Polish | Not measured | 1449 | Only Qwen3.7 Plus measured |
| LMArena Text: multi-turn | Not measured | 1459 | Only Qwen3.7 Plus measured |
| LMArena Text: longer queries | Not measured | 1454 | Only Qwen3.7 Plus measured |
| LMArena Text: writing and language | Not measured | 1437 | Only Qwen3.7 Plus measured |
| LMArena Text: entertainment and media | Not measured | 1422 | Only Qwen3.7 Plus measured |
| LMArena Vision: English | Not measured | 1280 | Only Qwen3.7 Plus measured |
| LMArena Vision: Chinese | Not measured | 1332 | Only Qwen3.7 Plus measured |
| LMArena Vision: reading text | Not measured | 1288 | Only Qwen3.7 Plus measured |
| LMArena Vision: humor | Not measured | 1261 | Only Qwen3.7 Plus measured |
| LMArena Vision: creative writing | Not measured | 1258 | Only Qwen3.7 Plus measured |
| LMArena Document | Not measured | 1444 | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus | 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 Plus costs less
Repository review
50K input + 3K output tokens
Qwen3.7 Plus costs less
Agent loop
200K input + 10K output tokens
Qwen3.7 Plus 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 | Qwen3.5 Plus 2026-04-20 | Qwen3.7 Plus |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | No public weights listed | No public weights listed |
| Released | April 27, 2026 | June 3, 2026 |
| Context window | 1M | 1M |
| Input $/Mtok | $0.30 | $0.32 |
| Output $/Mtok | $1.80 | $1.28 |
| Coding index | 39.5 | 33.2 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.35 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.5 Plus 2026-04-20 better than Qwen3.7 Plus for coding?
Pick Qwen3.5 Plus 2026-04-20 for coding: it scores 39.5 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for output tokens 1.4x cheaper ($1.28 vs $1.80 per million) and work measured by Vibe Code Bench (Vals AI) or Epoch Capabilities Index, where it leads.
Which is cheaper, Qwen3.5 Plus 2026-04-20 or Qwen3.7 Plus?
Qwen3.5 Plus 2026-04-20 costs $0.30 per million input tokens and $1.80 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for Qwen3.5 Plus 2026-04-20 only.
Which has the bigger context window, Qwen3.5 Plus 2026-04-20 or Qwen3.7 Plus?
Neither: both take 1M tokens.
How many benchmarks is the Qwen3.5 Plus 2026-04-20 vs Qwen3.7 Plus comparison based on?
9 benchmarks have a result for both models as of October 22, 2026. Qwen3.5 Plus 2026-04-20's coding index rests on 2 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.