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Qwen3.5 397B A17B vs Qwen3.6 Plus

Qwen3.6 Plus leads Qwen3.5 397B A17B on the Artificial Analysis Intelligence Index, 27.0 to 21.4, and Qwen3.6 Plus costs 1.2x less per output token ($1.95 vs $2.34 per million). Updated October 22, 2026; 53 benchmarks have a result for both.

Replace Qwen3.5 397B A17B Replace Qwen3.6 Plus
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.1
Output $/M
$2.34
24
Qwen3.6 PlusQwen
Coding
44.1
Overall
56.2
Output $/M
$1.95
29
vs boards won of 53 shared

Qwen3.5 397B A17B or Qwen3.6 Plus: which to pick

Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding.

Pick Qwen3.5 397B A17B for work measured by LMArena Text: software and IT or GPQA Diamond (Artificial Analysis run), where it leads.

Model AQwen3.5 397B A17BQwenNot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.6 PlusQwen44.1/1003 independent benchmarks$1.19 per solved task
Shared results
53
Qwen3.5 397B A17B only
12
Qwen3.6 Plus only
30
Like-for-like categories
8 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
Qwen3.5 397B A17B not benchmarked, Qwen3.6 Plus 44.1 from 3 benchmarks.
Widest category
Web design, 6.6 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: Qwen3.5 397B A17B 1388 against Qwen3.6 Plus 1454, 11.0 points apart on a 0 to 100 scale.
Output price
Qwen3.5 397B A17B $2.34 against Qwen3.6 Plus $1.95 per million output tokens, 1.2x apart.
Context window
Qwen3.5 397B A17B takes 262K tokens, Qwen3.6 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.

Boards won, where both have a result
CategoryQwen3.5 397B A17BBarsQwen3.6 PlusTies
Coding16
Intelligence02
Agentic work01
Reasoning43
Math22
Knowledge40
Web design07
General138
All shared boards2429
CodingLike-for-likeSix of these boards feed the Vibe Coding Index16
Coding benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
LMArena WebDev14001461Qwen3.6 Plus
AA Coding IndexNot measured54.5Only Qwen3.6 Plus measured
LiveCodeBench (Vals AI)Not measured86.0%Only Qwen3.6 Plus measured
SWE-bench Verified (Vals AI)Not measured73.4%Only Qwen3.6 Plus measured
Vibe Code Bench (Vals AI)Not measured25.6%Only Qwen3.6 Plus measured
Code migration (Vals AI)Not measured11.1%Only Qwen3.6 Plus measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.6 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured53.2%Only Qwen3.6 Plus measured
SciCode44.8%Not measuredOnly Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)40.9%43.9%Qwen3.6 Plus
ALE-Bench621.9670.1Qwen3.6 Plus
LMArena Text: coding14641467Qwen3.6 Plus
LMArena Text: software and IT14631462Qwen3.5 397B A17B
LMArena WebDev: React13881454Qwen3.6 Plus
LMArena WebDev: HTML14101463Qwen3.6 Plus
LMArena WebDev: from an imageNot measured1472Only Qwen3.6 Plus measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
AA Intelligence Index21.427.0Qwen3.6 Plus
Epoch Capabilities Index146.8147.3Qwen3.6 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
Finance Agent (Vals AI)Not measured40.9%Only Qwen3.6 Plus measured
Tax Agent Bench (Vals AI)Not measured7.7%Only Qwen3.6 Plus measured
Legal Research Bench (Vals AI)Not measured14.9%Only Qwen3.6 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured32.9%Only Qwen3.6 Plus measured
τ²-Bench Telecom95.6%97.7%Qwen3.6 Plus
APEX-Agents24.9%Not measuredOnly Qwen3.5 397B A17B measured
Vending-Bench 2Not measured$5,115Only Qwen3.6 Plus measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index43
Reasoning benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
GPQA DiamondNot measured87.4%Only Qwen3.6 Plus measured
MMMU Pro (Vals AI)Not measured84.2%Only Qwen3.6 Plus measured
GPQA Diamond (Artificial Analysis run)89.3%88.2%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)29.0%27.8%Qwen3.5 397B A17B
GPQA Diamond (Epoch AI run)86.4%88.4%Qwen3.6 Plus
Chess puzzlesNot measured14.0%Only Qwen3.6 Plus measured
Mystery game puzzles18.0%12.0%Qwen3.5 397B A17B
LMArena Text: hard prompts14481448Qwen3.6 Plus
LMArena Text: expert14621454Qwen3.5 397B A17B
LMArena Text: hard prompts in English14501455Qwen3.6 Plus
LMArena Vision: diagrams1277Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: homework1292Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index22
Math benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
AIMENot measured94.6%Only Qwen3.6 Plus measured
OTIS Mock AIME88.9%93.3%Qwen3.6 Plus
FrontierMath, tiers 1 to 331.2%38.2%Qwen3.6 Plus
LMArena Text: math14531449Qwen3.5 397B A17B
LMArena Text: mathematical work14541448Qwen3.5 397B A17B
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
MMLU ProNot measured87.7%Only Qwen3.6 Plus measured
LegalBench (Vals AI)Not measured84.2%Only Qwen3.6 Plus measured
CaseLaw (Vals AI)Not measured51.5%Only Qwen3.6 Plus measured
CorpFin (Vals AI)Not measured61.9%Only Qwen3.6 Plus measured
TaxEval (Vals AI)Not measured74.7%Only Qwen3.6 Plus measured
MortgageTax (Vals AI)Not measured68.0%Only Qwen3.6 Plus measured
MedCode (Vals AI)Not measured36.9%Only Qwen3.6 Plus measured
SimpleQA VerifiedNot measured44.1%Only Qwen3.6 Plus measured
LMArena Text: science14571439Qwen3.5 397B A17B
LMArena Text: medicine and healthcare14551442Qwen3.5 397B A17B
LMArena Text: legal and government14411437Qwen3.5 397B A17B
LMArena Text: business and finance14351430Qwen3.5 397B A17B
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
Design Arena: websites11901243Qwen3.6 Plus
Design Arena: UI components11601230Qwen3.6 Plus
Design Arena: game dev11401211Qwen3.6 Plus
Design Arena: data viz11751228Qwen3.6 Plus
Design Arena: 3D11601202Qwen3.6 Plus
Design Arena: all code categories11791236Qwen3.6 Plus
Design Arena: SVG11391161Qwen3.6 Plus
Design Arena: ASCII artNot measured1113Only Qwen3.6 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index138
General benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
SAGE (Vals AI)Not measured44.9%Only Qwen3.6 Plus measured
MedScribe (Vals AI)Not measured77.0%Only Qwen3.6 Plus measured
Vals Multimodal IndexNot measured51.5%Only Qwen3.6 Plus measured
IFBench78.8%75.2%Qwen3.5 397B A17B
Long context reasoning (AA-LCR)77.3%78.3%Qwen3.6 Plus
DTBench87.5%81.9%Qwen3.5 397B A17B
LMCA37.9%33.1%Qwen3.5 397B A17B
CL-benchNot measured20.3%Only Qwen3.6 Plus measured
LMArena Text14371436Qwen3.5 397B A17B
LMArena Text: instruction following14241424Qwen3.6 Plus
LMArena Text: creative writing14021404Qwen3.6 Plus
LMArena Vision1262Not measuredOnly Qwen3.5 397B A17B measured
LMArena Text: English14431445Qwen3.6 Plus
LMArena Text: non-English14301424Qwen3.5 397B A17B
LMArena Text: Chinese14981477Qwen3.5 397B A17B
LMArena Text: German14451451Qwen3.6 Plus
LMArena Text: Japanese14291390Qwen3.5 397B A17B
LMArena Text: Korean13841379Qwen3.5 397B A17B
LMArena Text: French14621455Qwen3.5 397B A17B
LMArena Text: Spanish14411432Qwen3.5 397B A17B
LMArena Text: Russian14301434Qwen3.6 Plus
LMArena Text: Polish14471433Qwen3.5 397B A17B
LMArena Text: multi-turn14461438Qwen3.5 397B A17B
LMArena Text: longer queries14411439Qwen3.5 397B A17B
LMArena Text: writing and language14151418Qwen3.6 Plus
LMArena Text: entertainment and media13991402Qwen3.6 Plus
LMArena Vision: English1268Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: Chinese1314Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: reading text1271Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: humor1262Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: captioning1230Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: recognizing things1265Not measuredOnly Qwen3.5 397B A17B measured
LMArena Vision: creative writing1260Not measuredOnly Qwen3.5 397B A17B measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.5 397B A17B and Qwen3.6 Plus
BenchmarkQwen3.5 397B A17BQwen3.6 PlusLeader
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

Qwen3.5 397B A17B$0.0016Fits in one request
Qwen3.6 Plus$0.0013Fits in one request

Qwen3.6 Plus costs less

Repository review

50K input + 3K output tokens

Qwen3.5 397B A17B$0.027Fits in one request
Qwen3.6 Plus$0.022Fits in one request

Qwen3.6 Plus costs less

Agent loop

200K input + 10K output tokens

Qwen3.5 397B A17B$0.101Fits in one request
Qwen3.6 Plus$0.085Fits in one request

Qwen3.6 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 Qwen3.5 397B A17B and Qwen3.6 Plus
SpecificationQwen3.5 397B A17BQwen3.6 Plus
MakerQwenQwen
WeightsOpen weightsNo public weights listed
ReleasedFebruary 16, 2026April 2, 2026
Context window262K1M
Input $/Mtok$0.39$0.325
Output $/Mtok$2.34$1.95
Coding indexNot benchmarked44.1
Independent measurements behind it13
Cost per solved taskNot computable$1.19
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5 397B A17B better than Qwen3.6 Plus for coding?

Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; Qwen3.5 397B A17B has none, so the two cannot be ranked on coding. Pick Qwen3.5 397B A17B for work measured by LMArena Text: software and IT or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Qwen3.5 397B A17B or Qwen3.6 Plus?

Qwen3.5 397B A17B costs $0.39 per million input tokens and $2.34 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Cost per solved task is known for Qwen3.6 Plus only.

Which has the bigger context window, Qwen3.5 397B A17B or Qwen3.6 Plus?

Qwen3.6 Plus, with 1M tokens against 262K.

How many benchmarks is the Qwen3.5 397B A17B vs Qwen3.6 Plus comparison based on?

53 benchmarks have a result for both models as of October 22, 2026. Qwen3.5 397B A17B's coding index rests on 1 independent benchmark and Qwen3.6 Plus's on 3. Where only one model has a result, the page says so instead of naming a winner.

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