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Qwen3.5-35B-A3B vs Qwen3.6 35B A3B

Qwen3.5-35B-A3B leads Qwen3.6 35B A3B on the Artificial Analysis Intelligence Index, 19.3 to 18.2, and Qwen3.6 35B A3B costs 1.3x less per output token ($1.00 vs $1.30 per million). Updated October 22, 2026; 12 benchmarks have a result for both.

Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
5
Qwen3.6 35B A3BQwen
Coding
No data
Overall
45.0
Output $/M
$1.00
7
vs boards won of 12 shared

Qwen3.5-35B-A3B or Qwen3.6 35B A3B: which to pick

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

Pick Qwen3.5-35B-A3B for work measured by Terminal-Bench Hard (Artificial Analysis run) or Epoch Capabilities Index, where it leads.

Shared results
12
Qwen3.5-35B-A3B only
34
Qwen3.6 35B A3B only
8
Like-for-like categories
6 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
Qwen3.5-35B-A3B not benchmarked, Qwen3.6 35B A3B not benchmarked.
Widest category
Math, 16.7 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: Qwen3.5-35B-A3B 70.0% against Qwen3.6 35B A3B 86.7%, 16.7 points apart on a 0 to 100 scale.
Output price
Qwen3.5-35B-A3B $1.30 against Qwen3.6 35B A3B $1.00 per million output tokens, 1.3x apart.
Context window
Both take 262K tokens.

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
CategoryQwen3.5-35B-A3BBarsQwen3.6 35B A3BTies
Coding01
Intelligence11
Agentic work01
Reasoning12
Math01
General31
All shared boards57
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
LMArena WebDev1254Not measuredOnly Qwen3.5-35B-A3B measured
AA Coding IndexNot measured41.9Only Qwen3.6 35B A3B measured
SciCodeNot measured36.6%Only Qwen3.6 35B A3B measured
Terminal-Bench Hard (Artificial Analysis run)26.5%34.8%Qwen3.6 35B A3B
Terminal-BenchNot measured24.6%Only Qwen3.6 35B A3B measured
WeirdMLNot measured34.5%Only Qwen3.6 35B A3B measured
ALE-Bench221.8Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: coding1410Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: software and IT1415Not measuredOnly Qwen3.5-35B-A3B measured
LMArena WebDev: React1238Not measuredOnly Qwen3.5-35B-A3B measured
LMArena WebDev: HTML1301Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
AA Intelligence Index19.318.2Qwen3.5-35B-A3B
Epoch Capabilities Index142.5143.7Qwen3.6 35B A3B
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
AA Agentic IndexNot measured13.1Only Qwen3.6 35B A3B measured
τ²-Bench Telecom89.2%95.3%Qwen3.6 35B A3B
Vending-Bench 2$463Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index12
Reasoning benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
GPQA Diamond (Artificial Analysis run)84.5%84.1%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)21.0%22.2%Qwen3.6 35B A3B
GPQA Diamond (Epoch AI run)83.5%84.8%Qwen3.6 35B A3B
Mystery game puzzlesNot measured22.0%Only Qwen3.6 35B A3B measured
LMArena Text: hard prompts1400Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: expert1408Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: hard prompts in English1411Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
OTIS Mock AIME70.0%86.7%Qwen3.6 35B A3B
FrontierMath, tiers 1 to 3Not measured20.4%Only Qwen3.6 35B A3B measured
LMArena Text: math1404Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: mathematical work1410Not measuredOnly Qwen3.5-35B-A3B measured
MathArena14.7%Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
LMArena Text: science1413Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: medicine and healthcare1421Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: legal and government1399Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: business and finance1394Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index31
General benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
IFBench72.5%64.4%Qwen3.5-35B-A3B
Long context reasoning (AA-LCR)72.0%71.7%Qwen3.5-35B-A3B
DTBench80.0%73.9%Qwen3.5-35B-A3B
LMCA29.5%29.7%Qwen3.6 35B A3B
Surface Evolver BenchNot measured44.4%Only Qwen3.6 35B A3B measured
LMArena Text1395Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: instruction following1379Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: creative writing1347Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: English1407Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: non-English1378Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: Chinese1457Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: German1367Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: Japanese1326Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: Korean1355Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: French1412Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: Spanish1390Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: Russian1376Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: Polish1385Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: multi-turn1390Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: longer queries1389Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: writing and language1365Not measuredOnly Qwen3.5-35B-A3B measured
LMArena Text: entertainment and media1347Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.5-35B-A3B and Qwen3.6 35B A3B
BenchmarkQwen3.5-35B-A3BQwen3.6 35B A3BLeader
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

Qwen3.5-35B-A3B$0.0008Fits in one request
Qwen3.6 35B A3B$0.0006Fits in one request

Qwen3.6 35B A3B costs less

Repository review

50K input + 3K output tokens

Qwen3.5-35B-A3B$0.012Fits in one request
Qwen3.6 35B A3B$0.0080Fits in one request

Qwen3.6 35B A3B costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-35B-A3B$0.045Fits in one request
Qwen3.6 35B A3B$0.030Fits in one request

Qwen3.6 35B A3B 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 Qwen3.5-35B-A3B and Qwen3.6 35B A3B
SpecificationQwen3.5-35B-A3BQwen3.6 35B A3B
MakerQwenQwen
WeightsOpen weightsOpen weights
ReleasedFebruary 25, 2026April 27, 2026
Context window262K262K
Input $/Mtok$0.1625$0.10
Output $/Mtok$1.30$1.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-35B-A3B better than Qwen3.6 35B A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen3.5-35B-A3B for work measured by Terminal-Bench Hard (Artificial Analysis run) or Epoch Capabilities Index, where it leads.

Which is cheaper, Qwen3.5-35B-A3B or Qwen3.6 35B A3B?

Qwen3.5-35B-A3B costs $0.1625 per million input tokens and $1.30 per million output tokens; Qwen3.6 35B A3B costs $0.10 and $1.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen3.5-35B-A3B or Qwen3.6 35B A3B?

Neither: both take 262K tokens.

How many benchmarks is the Qwen3.5-35B-A3B vs Qwen3.6 35B A3B comparison based on?

12 benchmarks have a result for both models as of October 22, 2026. Qwen3.5-35B-A3B's coding index rests on 1 independent benchmark and Qwen3.6 35B A3B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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