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Qwen3.5-122B-A10B vs Qwen3.6 Plus

Qwen3.6 Plus leads Qwen3.5-122B-A10B on the Artificial Analysis Intelligence Index, 27.0 to 17.7, at about the same output price ($1.95 vs $2.08 per million). Updated October 22, 2026; 42 benchmarks have a result for both.

Replace Qwen3.5-122B-A10B Replace Qwen3.6 Plus
Qwen3.5-122B-A10BQwen
Coding
No data
Overall
No data
Output $/M
$2.08
3
Qwen3.6 PlusQwen
Coding
44.1
Overall
56.2
Output $/M
$1.95
39
vs boards won of 42 shared

Qwen3.5-122B-A10B or Qwen3.6 Plus: which to pick

Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; Qwen3.5-122B-A10B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-122B-A10B for work measured by Mystery game puzzles or IFBench, where it leads.

Model AQwen3.5-122B-A10BQwenNot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.6 PlusQwen44.1/1003 independent benchmarks$1.19 per solved task
Shared results
42
Qwen3.5-122B-A10B only
9
Qwen3.6 Plus only
41
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.

At a glance

Coding index
Qwen3.5-122B-A10B not benchmarked, Qwen3.6 Plus 44.1 from 3 benchmarks.
Widest category
Coding, 11.9 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: Qwen3.5-122B-A10B 1351 against Qwen3.6 Plus 1463, 18.5 points apart on a 0 to 100 scale.
Output price
Qwen3.5-122B-A10B $2.08 against Qwen3.6 Plus $1.95 per million output tokens, 1.1x apart.
Context window
Qwen3.5-122B-A10B 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
CategoryQwen3.5-122B-A10BBarsQwen3.6 PlusTies
Coding07
Intelligence01
Agentic work01
Reasoning15
Math02
Knowledge04
General219
All shared boards339
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
Coding benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 PlusLeader
LMArena WebDev13611461Qwen3.6 Plus
AA Coding Index43.354.5Qwen3.6 Plus
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
SciCode39.7%Not measuredOnly Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)31.1%43.9%Qwen3.6 Plus
ALE-BenchNot measured670.1Only Qwen3.6 Plus measured
LMArena Text: coding14361467Qwen3.6 Plus
LMArena Text: software and IT14361462Qwen3.6 Plus
LMArena WebDev: React13531454Qwen3.6 Plus
LMArena WebDev: HTML13511463Qwen3.6 Plus
LMArena WebDev: from an imageNot measured1472Only Qwen3.6 Plus measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 PlusLeader
AA Intelligence Index17.727.0Qwen3.6 Plus
Epoch Capabilities IndexNot measured147.3Only Qwen3.6 Plus measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 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 Telecom93.6%97.7%Qwen3.6 Plus
Vending-Bench 2Not measured$5,115Only Qwen3.6 Plus measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
Reasoning benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 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)85.7%88.2%Qwen3.6 Plus
Humanity's Last Exam (Artificial Analysis run)25.2%27.8%Qwen3.6 Plus
GPQA Diamond (Epoch AI run)Not measured88.4%Only Qwen3.6 Plus measured
Chess puzzlesNot measured14.0%Only Qwen3.6 Plus measured
Mystery game puzzles17.0%12.0%Qwen3.5-122B-A10B
LMArena Text: hard prompts14211448Qwen3.6 Plus
LMArena Text: expert14311454Qwen3.6 Plus
LMArena Text: hard prompts in English14311455Qwen3.6 Plus
LMArena Vision: diagrams1249Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: homework1261Not measuredOnly Qwen3.5-122B-A10B measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 PlusLeader
AIMENot measured94.6%Only Qwen3.6 Plus measured
OTIS Mock AIMENot measured93.3%Only Qwen3.6 Plus measured
FrontierMath, tiers 1 to 3Not measured38.2%Only Qwen3.6 Plus measured
LMArena Text: math14311449Qwen3.6 Plus
LMArena Text: mathematical work14311448Qwen3.6 Plus
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 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: science14321439Qwen3.6 Plus
LMArena Text: medicine and healthcare14231442Qwen3.6 Plus
LMArena Text: legal and government14221437Qwen3.6 Plus
LMArena Text: business and finance14141430Qwen3.6 Plus
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 PlusLeader
Design Arena: websitesNot measured1243Only Qwen3.6 Plus measured
Design Arena: UI componentsNot measured1230Only Qwen3.6 Plus measured
Design Arena: game devNot measured1211Only Qwen3.6 Plus measured
Design Arena: data vizNot measured1228Only Qwen3.6 Plus measured
Design Arena: 3DNot measured1202Only Qwen3.6 Plus measured
Design Arena: all code categoriesNot measured1235Only Qwen3.6 Plus measured
Design Arena: SVGNot measured1160Only Qwen3.6 Plus measured
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 index219
General benchmarks for Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 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
IFBench75.7%75.2%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)76.3%78.3%Qwen3.6 Plus
DTBench84.3%81.9%Qwen3.5-122B-A10B
LMCA32.2%33.1%Qwen3.6 Plus
CL-benchNot measured20.3%Only Qwen3.6 Plus measured
LMArena Text14171436Qwen3.6 Plus
LMArena Text: instruction following13991424Qwen3.6 Plus
LMArena Text: creative writing13681404Qwen3.6 Plus
LMArena Vision1244Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Text: English14281445Qwen3.6 Plus
LMArena Text: non-English14011424Qwen3.6 Plus
LMArena Text: Chinese14631477Qwen3.6 Plus
LMArena Text: German14251451Qwen3.6 Plus
LMArena Text: Japanese13671390Qwen3.6 Plus
LMArena Text: Korean13531379Qwen3.6 Plus
LMArena Text: French14431455Qwen3.6 Plus
LMArena Text: Spanish14251432Qwen3.6 Plus
LMArena Text: Russian14001434Qwen3.6 Plus
LMArena Text: Polish13981433Qwen3.6 Plus
LMArena Text: multi-turn14161438Qwen3.6 Plus
LMArena Text: longer queries14101439Qwen3.6 Plus
LMArena Text: writing and language13871418Qwen3.6 Plus
LMArena Text: entertainment and media13661402Qwen3.6 Plus
LMArena Vision: English1249Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: Chinese1301Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: reading text1251Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: humor1243Not measuredOnly Qwen3.5-122B-A10B measured
LMArena Vision: creative writing1220Not measuredOnly Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B and Qwen3.6 Plus
BenchmarkQwen3.5-122B-A10BQwen3.6 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

Qwen3.5-122B-A10B$0.0013Fits in one request
Qwen3.6 Plus$0.0013Fits in one request

Same cost

Repository review

50K input + 3K output tokens

Qwen3.5-122B-A10B$0.019Fits in one request
Qwen3.6 Plus$0.022Fits in one request

Qwen3.5-122B-A10B costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-122B-A10B$0.073Fits in one request
Qwen3.6 Plus$0.085Fits in one request

Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B and Qwen3.6 Plus
SpecificationQwen3.5-122B-A10BQwen3.6 Plus
MakerQwenQwen
WeightsOpen weightsNo public weights listed
ReleasedFebruary 25, 2026April 2, 2026
Context window262K1M
Input $/Mtok$0.26$0.325
Output $/Mtok$2.08$1.95
Coding indexNot benchmarked44.1
Independent measurements behind it13
Cost per solved taskNot computable$1.19
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-122B-A10B better than Qwen3.6 Plus for coding?

Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; Qwen3.5-122B-A10B has none, so the two cannot be ranked on coding. Pick Qwen3.5-122B-A10B for work measured by Mystery game puzzles or IFBench, where it leads.

Which is cheaper, Qwen3.5-122B-A10B or Qwen3.6 Plus?

Qwen3.5-122B-A10B costs $0.26 per million input tokens and $2.08 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, Qwen3.5-122B-A10B or Qwen3.6 Plus?

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

How many benchmarks is the Qwen3.5-122B-A10B vs Qwen3.6 Plus comparison based on?

42 benchmarks have a result for both models as of October 22, 2026. Qwen3.5-122B-A10B'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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