Qwen-Plus vs Qwen3.5-27B
Qwen-Plus costs 2.0x less per output token than Qwen3.5-27B ($0.78 vs $1.56 per million). Updated October 21, 2026; 25 benchmarks have a result for both.
Qwen-Plus or Qwen3.5-27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen-Plus for output tokens 2.0x cheaper ($0.78 vs $1.56 per million) and a larger context window (1M against 262K tokens).
- Shared results
- 25
- Qwen-Plus only
- 3
- Qwen3.5-27B only
- 28
- Like-for-like categories
- 5 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
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.5-27B has a AA Intelligence Index result, 22.9.
Directional only
Long documents
Listed context window
Qwen-Plus
Qwen-Plus takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen-Plus
Qwen-Plus $0.0006, Qwen3.5-27B $0.0010 per turn.
List prices
At a glance
- Coding index
- Qwen-Plus not benchmarked, Qwen3.5-27B not benchmarked.
- Widest category
- Math, 16.7 points apart on average over 2 shared benchmarks.
- Widest single gap
- LMArena Text: Chinese: Qwen-Plus 1347 against Qwen3.5-27B 1478, 21.9 points apart on a 0 to 100 scale.
- Output price
- Qwen-Plus $0.78 against Qwen3.5-27B $1.56 per million output tokens, 2.0x apart.
- Context window
- Qwen-Plus takes 1M tokens, Qwen3.5-27B 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 | Qwen-Plus | Bars | Qwen3.5-27B | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Reasoning | 0 | 3 | ||
| Math | 0 | 2 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 14 | ||
| All shared boards | 0 | 25 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| LMArena WebDev | Not measured | 1358 | Only Qwen3.5-27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 32.6% | Only Qwen3.5-27B measured |
| WeirdML | Not measured | 39.5% | Only Qwen3.5-27B measured |
| ALE-Bench | Not measured | 349.4 | Only Qwen3.5-27B measured |
| LMArena Text: coding | 1328 | 1427 | Qwen3.5-27B |
| LMArena Text: software and IT | 1343 | 1431 | Qwen3.5-27B |
| LMArena WebDev: React | Not measured | 1346 | Only Qwen3.5-27B measured |
| LMArena WebDev: HTML | Not measured | 1386 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 22.9 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | Not measured | 93.9% | Only Qwen3.5-27B measured |
| Vending-Bench 2 | Not measured | $202 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.8% | Only Qwen3.5-27B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.9% | Only Qwen3.5-27B measured |
| GPQA Diamond (Epoch AI run) | 48.1% | Not measured | Only Qwen-Plus measured |
| LMArena Text: hard prompts | 1317 | 1415 | Qwen3.5-27B |
| LMArena Text: expert | 1328 | 1427 | Qwen3.5-27B |
| LMArena Text: hard prompts in English | 1333 | 1429 | Qwen3.5-27B |
| LMArena Vision: diagrams | Not measured | 1249 | Only Qwen3.5-27B measured |
| LMArena Vision: homework | Not measured | 1256 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 14 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 17.8% | Not measured | Only Qwen-Plus measured |
| MATH level 5 | 65.3% | Not measured | Only Qwen-Plus measured |
| LMArena Text: math | 1326 | 1429 | Qwen3.5-27B |
| LMArena Text: mathematical work | 1332 | 1429 | Qwen3.5-27B |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| LMArena Text: science | 1352 | 1437 | Qwen3.5-27B |
| LMArena Text: medicine and healthcare | 1350 | 1425 | Qwen3.5-27B |
| LMArena Text: legal and government | 1349 | 1405 | Qwen3.5-27B |
| LMArena Text: business and finance | 1303 | 1399 | Qwen3.5-27B |
| Neither model has a result on the other 14 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
| Benchmark | Qwen-Plus | Qwen3.5-27B | Leader |
|---|---|---|---|
| IFBench | Not measured | 75.6% | Only Qwen3.5-27B measured |
| Long context reasoning (AA-LCR) | Not measured | 77.7% | Only Qwen3.5-27B measured |
| DTBench | 81.1% | 82.4% | Qwen3.5-27B |
| LMCA | 24.0% | 34.0% | Qwen3.5-27B |
| LMArena Text | 1326 | 1409 | Qwen3.5-27B |
| LMArena Text: instruction following | 1303 | 1393 | Qwen3.5-27B |
| LMArena Text: creative writing | 1292 | 1362 | Qwen3.5-27B |
| LMArena Vision | Not measured | 1241 | Only Qwen3.5-27B measured |
| LMArena Text: English | 1339 | 1425 | Qwen3.5-27B |
| LMArena Text: non-English | 1310 | 1390 | Qwen3.5-27B |
| LMArena Text: Chinese | 1347 | 1478 | Qwen3.5-27B |
| LMArena Text: German | Not measured | 1392 | Only Qwen3.5-27B measured |
| LMArena Text: Japanese | 1251 | 1346 | Qwen3.5-27B |
| LMArena Text: Korean | Not measured | 1359 | Only Qwen3.5-27B measured |
| LMArena Text: French | Not measured | 1410 | Only Qwen3.5-27B measured |
| LMArena Text: Spanish | Not measured | 1407 | Only Qwen3.5-27B measured |
| LMArena Text: Russian | 1323 | 1390 | Qwen3.5-27B |
| LMArena Text: Polish | Not measured | 1375 | Only Qwen3.5-27B measured |
| LMArena Text: multi-turn | 1336 | 1410 | Qwen3.5-27B |
| LMArena Text: longer queries | 1324 | 1413 | Qwen3.5-27B |
| LMArena Text: writing and language | 1296 | 1380 | Qwen3.5-27B |
| LMArena Text: entertainment and media | 1270 | 1363 | Qwen3.5-27B |
| LMArena Vision: English | Not measured | 1246 | Only Qwen3.5-27B measured |
| LMArena Vision: Chinese | Not measured | 1301 | Only Qwen3.5-27B measured |
| LMArena Vision: reading text | Not measured | 1246 | Only Qwen3.5-27B measured |
| LMArena Vision: humor | Not measured | 1227 | Only Qwen3.5-27B measured |
| LMArena Vision: captioning | Not measured | 1170 | Only Qwen3.5-27B measured |
| LMArena Vision: recognizing things | Not measured | 1210 | Only Qwen3.5-27B measured |
| LMArena Vision: creative writing | Not measured | 1224 | Only Qwen3.5-27B measured |
| Neither model has a result on the other 17 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Qwen-Plus | Qwen3.5-27B | 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
Qwen-Plus costs less
Repository review
50K input + 3K output tokens
Qwen3.5-27B costs less
Agent loop
200K input + 10K output tokens
Qwen3.5-27B 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 | Qwen-Plus | Qwen3.5-27B |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | No public weights listed | Open weights |
| Released | February 1, 2025 | February 25, 2026 |
| Context window | 1M | 262K |
| Input $/Mtok | $0.26 | $0.195 |
| Output $/Mtok | $0.78 | $1.56 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Qwen-Plus better than Qwen3.5-27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen-Plus for output tokens 2.0x cheaper ($0.78 vs $1.56 per million) and a larger context window (1M against 262K tokens).
Which is cheaper, Qwen-Plus or Qwen3.5-27B?
Qwen-Plus costs $0.26 per million input tokens and $0.78 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for neither of them.
Which has the bigger context window, Qwen-Plus or Qwen3.5-27B?
Qwen-Plus, with 1M tokens against 262K.
How many benchmarks is the Qwen-Plus vs Qwen3.5-27B comparison based on?
25 benchmarks have a result for both models as of October 21, 2026. Qwen-Plus's coding index rests on 0 independent benchmarks and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.