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Qwen-Plus vs Qwen3.5 397B A17B

Qwen-Plus costs 3.0x less per output token than Qwen3.5 397B A17B ($0.78 vs $2.34 per million). Updated October 22, 2026; 27 benchmarks have a result for both.

Qwen-PlusQwen
Coding
No data
Overall
No data
Output $/M
$0.78
0
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
27
vs boards won of 27 shared

Qwen-Plus or Qwen3.5 397B A17B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Qwen-Plus for output tokens 3.0x cheaper ($0.78 vs $2.34 per million) and a larger context window (1M against 262K tokens).

Shared results
27
Qwen-Plus only
1
Qwen3.5 397B A17B only
38
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.

At a glance

Coding index
Qwen-Plus not benchmarked, Qwen3.5 397B A17B not benchmarked.
Widest category
Math, 37.5 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: Qwen-Plus 17.8% against Qwen3.5 397B A17B 88.9%, 71.1 points apart on a 0 to 100 scale.
Output price
Qwen-Plus $0.78 against Qwen3.5 397B A17B $2.34 per million output tokens, 3.0x apart.
Context window
Qwen-Plus takes 1M tokens, Qwen3.5 397B A17B 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.

Boards won, where both have a result
CategoryQwen-PlusBarsQwen3.5 397B A17BTies
Coding02
Reasoning04
Math03
Knowledge04
General014
All shared boards027
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
LMArena WebDevNot measured1400Only Qwen3.5 397B A17B measured
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured40.9%Only Qwen3.5 397B A17B measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: coding13281464Qwen3.5 397B A17B
LMArena Text: software and IT13431463Qwen3.5 397B A17B
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTMLNot measured1410Only Qwen3.5 397B A17B measured
Neither model has a result on the other 31 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
AA Intelligence IndexNot measured21.4Only Qwen3.5 397B A17B measured
Epoch Capabilities IndexNot measured146.8Only Qwen3.5 397B A17B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
τ²-Bench TelecomNot measured95.6%Only Qwen3.5 397B A17B measured
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
GPQA Diamond (Artificial Analysis run)Not measured89.3%Only Qwen3.5 397B A17B measured
Humanity's Last Exam (Artificial Analysis run)Not measured29.0%Only Qwen3.5 397B A17B measured
GPQA Diamond (Epoch AI run)48.1%86.4%Qwen3.5 397B A17B
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts13171448Qwen3.5 397B A17B
LMArena Text: expert13281462Qwen3.5 397B A17B
LMArena Text: hard prompts in English13331450Qwen3.5 397B A17B
LMArena Vision: diagramsNot measured1277Only Qwen3.5 397B A17B measured
LMArena Vision: homeworkNot measured1292Only Qwen3.5 397B A17B measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
OTIS Mock AIME17.8%88.9%Qwen3.5 397B A17B
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
MATH level 565.3%Not measuredOnly Qwen-Plus measured
LMArena Text: math13261453Qwen3.5 397B A17B
LMArena Text: mathematical work13321454Qwen3.5 397B A17B
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
LMArena Text: science13521457Qwen3.5 397B A17B
LMArena Text: medicine and healthcare13501455Qwen3.5 397B A17B
LMArena Text: legal and government13491441Qwen3.5 397B A17B
LMArena Text: business and finance13031435Qwen3.5 397B A17B
Neither model has a result on the other 14 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
Design Arena: websitesNot measured1190Only Qwen3.5 397B A17B measured
Design Arena: UI componentsNot measured1160Only Qwen3.5 397B A17B measured
Design Arena: game devNot measured1140Only Qwen3.5 397B A17B measured
Design Arena: data vizNot measured1175Only Qwen3.5 397B A17B measured
Design Arena: 3DNot measured1160Only Qwen3.5 397B A17B measured
Design Arena: all code categoriesNot measured1179Only Qwen3.5 397B A17B measured
Design Arena: SVGNot measured1139Only Qwen3.5 397B A17B measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index014
General benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
IFBenchNot measured78.8%Only Qwen3.5 397B A17B measured
Long context reasoning (AA-LCR)Not measured77.3%Only Qwen3.5 397B A17B measured
DTBench81.1%87.5%Qwen3.5 397B A17B
LMCA24.0%37.9%Qwen3.5 397B A17B
LMArena Text13261437Qwen3.5 397B A17B
LMArena Text: instruction following13031424Qwen3.5 397B A17B
LMArena Text: creative writing12921402Qwen3.5 397B A17B
LMArena VisionNot measured1262Only Qwen3.5 397B A17B measured
LMArena Text: English13391443Qwen3.5 397B A17B
LMArena Text: non-English13101430Qwen3.5 397B A17B
LMArena Text: Chinese13471498Qwen3.5 397B A17B
LMArena Text: GermanNot measured1445Only Qwen3.5 397B A17B measured
LMArena Text: Japanese12511429Qwen3.5 397B A17B
LMArena Text: KoreanNot measured1384Only Qwen3.5 397B A17B measured
LMArena Text: FrenchNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: SpanishNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: Russian13231430Qwen3.5 397B A17B
LMArena Text: PolishNot measured1447Only Qwen3.5 397B A17B measured
LMArena Text: multi-turn13361446Qwen3.5 397B A17B
LMArena Text: longer queries13241441Qwen3.5 397B A17B
LMArena Text: writing and language12961415Qwen3.5 397B A17B
LMArena Text: entertainment and media12701399Qwen3.5 397B A17B
LMArena Vision: EnglishNot measured1268Only Qwen3.5 397B A17B measured
LMArena Vision: ChineseNot measured1314Only Qwen3.5 397B A17B measured
LMArena Vision: reading textNot measured1271Only Qwen3.5 397B A17B measured
LMArena Vision: humorNot measured1262Only Qwen3.5 397B A17B measured
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B 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
Image generation benchmarks for Qwen-Plus and Qwen3.5 397B A17B
BenchmarkQwen-PlusQwen3.5 397B A17BLeader
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$0.0006Fits in one request
Qwen3.5 397B A17B$0.0016Fits in one request

Qwen-Plus costs less

Repository review

50K input + 3K output tokens

Qwen-Plus$0.015Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

Qwen-Plus costs less

Agent loop

200K input + 10K output tokens

Qwen-Plus$0.060Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

Qwen-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.

Specifications of Qwen-Plus and Qwen3.5 397B A17B
SpecificationQwen-PlusQwen3.5 397B A17B
MakerQwenQwen
WeightsNo public weights listedOpen weights
ReleasedFebruary 1, 2025February 16, 2026
Context window1M262K
Input $/Mtok$0.26$0.39
Output $/Mtok$0.78$2.34
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen-Plus better than Qwen3.5 397B A17B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen-Plus for output tokens 3.0x cheaper ($0.78 vs $2.34 per million) and a larger context window (1M against 262K tokens).

Which is cheaper, Qwen-Plus or Qwen3.5 397B A17B?

Qwen-Plus costs $0.26 per million input tokens and $0.78 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen-Plus or Qwen3.5 397B A17B?

Qwen-Plus, with 1M tokens against 262K.

How many benchmarks is the Qwen-Plus vs Qwen3.5 397B A17B comparison based on?

27 benchmarks have a result for both models as of October 22, 2026. Qwen-Plus's coding index rests on 0 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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