Qwen3.6 27B vs Qwen3.7 Plus
Qwen3.6 27B leads Qwen3.7 Plus on coding, 36.8 to 33.2 on the Vibe Coding Index, and Qwen3.7 Plus costs 2.1x less per output token ($1.28 vs $2.70 per million). Updated October 22, 2026; 20 benchmarks have a result for both.
Qwen3.6 27B or Qwen3.7 Plus: which to pick
Pick Qwen3.6 27B for coding: it scores 36.8 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.
Pick Qwen3.7 Plus for output tokens 2.1x cheaper ($1.28 vs $2.70 per million) and a larger context window (1M against 262K tokens).
- Shared results
- 20
- Qwen3.6 27B only
- 4
- Qwen3.7 Plus only
- 55
- Like-for-like categories
- 7 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
Qwen3.6 27B
Qwen3.6 27B scores 36.8 against 33.2.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Qwen3.7 Plus
Qwen3.7 Plus leads, 25.2 against 21.4.
Same board, both measured
Agentic work
AA Agentic Index
Qwen3.6 27B
Qwen3.6 27B leads, 18.5 against 17.5.
Same board, both measured
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
Qwen3.7 Plus
Qwen3.7 Plus takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.7 Plus
Qwen3.6 27B $0.0018, Qwen3.7 Plus $0.0010 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Qwen3.6 27B has the number, $1.30.
Directional only
At a glance
- Coding index
- Qwen3.6 27B 36.8 from 2 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
- Widest category
- Coding, 13.0 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Qwen3.6 27B 11.9% against Qwen3.7 Plus 46.4%, 34.5 points apart on a 0 to 100 scale.
- Output price
- Qwen3.6 27B $2.70 against Qwen3.7 Plus $1.28 per million output tokens, 2.1x apart.
- Context window
- Qwen3.6 27B takes 262K tokens, Qwen3.7 Plus 1M.
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 | Qwen3.6 27B | Bars | Qwen3.7 Plus | Ties |
|---|---|---|---|---|
| Coding | 0 | 4 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 2 | 0 | ||
| Reasoning | 0 | 4 | ||
| Math | 1 | 1 | ||
| Knowledge | 1 | 0 | ||
| General | 2 | 3 | ||
| All shared boards | 6 | 14 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Coding Index | 53.7 | 55.9 | Qwen3.7 Plus |
| SWE-bench Verified (Vals AI) | 70.0% | Not measured | Only Qwen3.6 27B measured |
| Vibe Code Bench (Vals AI) | 11.9% | 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 | 42.8% | 46.1% | Qwen3.7 Plus |
| Terminal-Bench Hard (Artificial Analysis run) | 34.8% | 47.0% | Qwen3.7 Plus |
| FrontierCode | Not measured | 10.2% | Only Qwen3.7 Plus 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 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 21.4 | 25.2 | Qwen3.7 Plus |
| Epoch Capabilities Index | 146.2 | 147.0 | Qwen3.7 Plus |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| AA Agentic Index | 18.5 | 17.5 | Qwen3.6 27B |
| 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 | 94.2% | 93.0% | Qwen3.6 27B |
| OSWorld 2.0 | Not measured | 2.8% | Only Qwen3.7 Plus measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 84.2% | 90.0% | Qwen3.7 Plus |
| Humanity's Last Exam (Artificial Analysis run) | 23.1% | 35.6% | Qwen3.7 Plus |
| GPQA Diamond (Epoch AI run) | 85.9% | 87.9% | Qwen3.7 Plus |
| Mystery game puzzles | 7.0% | 17.0% | Qwen3.7 Plus |
| 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 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| OTIS Mock AIME | 91.1% | 93.3% | Qwen3.7 Plus |
| FrontierMath, tiers 1 to 3 | 35.1% | 34.4% | Qwen3.6 27B |
| 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 index10
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 53.2% | Not measured | Only Qwen3.6 27B measured |
| CorpFin (Vals AI) | 62.3% | Not measured | Only Qwen3.6 27B measured |
| TaxEval (Vals AI) | 71.3% | Not measured | Only Qwen3.6 27B measured |
| MortgageTax (Vals AI) | 68.3% | 66.2% | Qwen3.6 27B |
| 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 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Qwen3.6 27B | 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 | 1261 | Only Qwen3.7 Plus measured |
| Design Arena: data viz | Not measured | 1276 | Only Qwen3.7 Plus measured |
| Design Arena: 3D | Not measured | 1238 | Only Qwen3.7 Plus measured |
| Design Arena: all code categories | Not measured | 1269 | Only Qwen3.7 Plus measured |
| Design Arena: SVG | Not measured | 1208 | 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 index23
| Benchmark | Qwen3.6 27B | Qwen3.7 Plus | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 45.6% | 39.3% | Qwen3.6 27B |
| Vals Multimodal Index | Not measured | 53.9% | Only Qwen3.7 Plus measured |
| IFBench | 67.6% | 78.0% | Qwen3.7 Plus |
| Long context reasoning (AA-LCR) | 77.3% | 73.0% | Qwen3.6 27B |
| DTBench | 78.1% | 84.0% | Qwen3.7 Plus |
| LMCA | 34.5% | 37.6% | Qwen3.7 Plus |
| 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 | Qwen3.6 27B | 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 | Qwen3.6 27B | Qwen3.7 Plus |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | No public weights listed |
| Released | April 27, 2026 | June 3, 2026 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.45 | $0.32 |
| Output $/Mtok | $2.70 | $1.28 |
| Coding index | 36.8 | 33.2 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.30 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen3.6 27B better than Qwen3.7 Plus for coding?
Pick Qwen3.6 27B for coding: it scores 36.8 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for output tokens 2.1x cheaper ($1.28 vs $2.70 per million) and a larger context window (1M against 262K tokens).
Which is cheaper, Qwen3.6 27B or Qwen3.7 Plus?
Qwen3.6 27B costs $0.45 per million input tokens and $2.70 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for Qwen3.6 27B only.
Which has the bigger context window, Qwen3.6 27B or Qwen3.7 Plus?
Qwen3.7 Plus, with 1M tokens against 262K.
How many benchmarks is the Qwen3.6 27B vs Qwen3.7 Plus comparison based on?
20 benchmarks have a result for both models as of October 22, 2026. Qwen3.6 27B'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.