Enter opens the highlighted result. Esc closes.

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

Qwen3.5-Flash costs 5.0x less per output token than Qwen3.5-35B-A3B ($0.26 vs $1.30 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace Qwen3.5-35B-A3B Replace Qwen3.5-Flash
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
16
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
21
vs boards won of 37 shared

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

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding.

Pick Qwen3.5-35B-A3B for work measured by LMArena WebDev or LMArena WebDev: React, where it leads.

Model AQwen3.5-35B-A3BQwenNot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
37
Qwen3.5-35B-A3B only
9
Qwen3.5-Flash only
18
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, Qwen3.5-Flash 41.1 from 2 benchmarks.
Widest category
Math, 5.1 points apart on average over 3 shared benchmarks.
Widest single gap
OTIS Mock AIME: Qwen3.5-35B-A3B 70.0% against Qwen3.5-Flash 84.4%, 14.4 points apart on a 0 to 100 scale.
Output price
Qwen3.5-35B-A3B $1.30 against Qwen3.5-Flash $0.26 per million output tokens, 5.0x apart.
Context window
Qwen3.5-35B-A3B takes 262K tokens, Qwen3.5-Flash 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
CategoryQwen3.5-35B-A3BBarsQwen3.5-FlashTies
Coding33
Intelligence01
Reasoning31
Math03
Knowledge22
General811
All shared boards1621
CodingLike-for-likeSix of these boards feed the Vibe Coding Index33
Coding benchmarks for Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
LMArena WebDev12541244Qwen3.5-35B-A3B
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)Not measured64.4%Only Qwen3.5-Flash measured
Terminal-Bench Hard (Artificial Analysis run)26.5%Not measuredOnly Qwen3.5-35B-A3B measured
ALE-Bench221.8265.9Qwen3.5-Flash
LMArena Text: coding14101412Qwen3.5-Flash
LMArena Text: software and IT14151416Qwen3.5-Flash
LMArena WebDev: React12381229Qwen3.5-35B-A3B
LMArena WebDev: HTML13011291Qwen3.5-35B-A3B
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
AA Intelligence Index19.3Not measuredOnly Qwen3.5-35B-A3B measured
Epoch Capabilities Index142.5143.5Qwen3.5-Flash
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
τ²-Bench Telecom89.2%Not measuredOnly Qwen3.5-35B-A3B measured
Vending-Bench 2$463Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index31
Reasoning benchmarks for Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
GPQA DiamondNot measured82.8%Only Qwen3.5-Flash measured
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)84.5%Not measuredOnly Qwen3.5-35B-A3B measured
Humanity's Last Exam (Artificial Analysis run)21.0%Not measuredOnly Qwen3.5-35B-A3B measured
GPQA Diamond (Epoch AI run)83.5%82.3%Qwen3.5-35B-A3B
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts14001403Qwen3.5-Flash
LMArena Text: expert14081407Qwen3.5-35B-A3B
LMArena Text: hard prompts in English14111409Qwen3.5-35B-A3B
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 Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
OTIS Mock AIME70.0%84.4%Qwen3.5-Flash
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
LMArena Text: math14041407Qwen3.5-Flash
LMArena Text: mathematical work14101413Qwen3.5-Flash
MathArena14.7%Not measuredOnly Qwen3.5-35B-A3B measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
Knowledge benchmarks for Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
MMLU ProNot measured84.1%Only Qwen3.5-Flash measured
LegalBench (Vals AI)Not measured84.3%Only Qwen3.5-Flash measured
CaseLaw (Vals AI)Not measured56.0%Only Qwen3.5-Flash measured
CorpFin (Vals AI)Not measured63.6%Only Qwen3.5-Flash measured
TaxEval (Vals AI)Not measured72.2%Only Qwen3.5-Flash measured
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedCode (Vals AI)Not measured33.0%Only Qwen3.5-Flash measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
LMArena Text: science14131415Qwen3.5-Flash
LMArena Text: medicine and healthcare14211407Qwen3.5-35B-A3B
LMArena Text: legal and government13991398Qwen3.5-35B-A3B
LMArena Text: business and finance13941394Qwen3.5-Flash
Neither model has a result on the other 8 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 Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index811
General benchmarks for Qwen3.5-35B-A3B and Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)Not measured70.6%Only Qwen3.5-Flash measured
IFBench72.5%Not measuredOnly Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)72.0%Not measuredOnly Qwen3.5-35B-A3B measured
DTBench80.0%82.9%Qwen3.5-Flash
LMCA29.5%29.1%Qwen3.5-35B-A3B
LMArena Text13951397Qwen3.5-Flash
LMArena Text: instruction following13791374Qwen3.5-35B-A3B
LMArena Text: creative writing13471343Qwen3.5-35B-A3B
LMArena Text: English14071404Qwen3.5-35B-A3B
LMArena Text: non-English13781385Qwen3.5-Flash
LMArena Text: Chinese14571445Qwen3.5-35B-A3B
LMArena Text: German13671390Qwen3.5-Flash
LMArena Text: Japanese13261369Qwen3.5-Flash
LMArena Text: Korean13551344Qwen3.5-35B-A3B
LMArena Text: French14121413Qwen3.5-Flash
LMArena Text: Spanish13901400Qwen3.5-Flash
LMArena Text: Russian13761380Qwen3.5-Flash
LMArena Text: Polish13851376Qwen3.5-35B-A3B
LMArena Text: multi-turn13901393Qwen3.5-Flash
LMArena Text: longer queries13891392Qwen3.5-Flash
LMArena Text: writing and language13651369Qwen3.5-Flash
LMArena Text: entertainment and media13471347Qwen3.5-35B-A3B
Neither model has a result on the other 25 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 Qwen3.5-Flash
BenchmarkQwen3.5-35B-A3BQwen3.5-FlashLeader
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
Qwen3.5-Flash$0.0002Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

Qwen3.5-35B-A3B$0.012Fits in one request
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-35B-A3B$0.045Fits in one request
Qwen3.5-Flash$0.016Fits in one request

Qwen3.5-Flash 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 Qwen3.5-Flash
SpecificationQwen3.5-35B-A3BQwen3.5-Flash
MakerQwenQwen
WeightsOpen weightsNo public weights listed
ReleasedFebruary 25, 2026February 25, 2026
Context window262K1M
Input $/Mtok$0.1625$0.065
Output $/Mtok$1.30$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it12
Cost per solved taskNot computable$0.40
SourceOpenRouter listingOpenRouter listing

Questions

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

Only Qwen3.5-Flash has a coding score, 41.1 on the Vibe Coding Index; Qwen3.5-35B-A3B has none, so the two cannot be ranked on coding. Pick Qwen3.5-35B-A3B for work measured by LMArena WebDev or LMArena WebDev: React, where it leads.

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

Qwen3.5-35B-A3B costs $0.1625 per million input tokens and $1.30 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.

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

Qwen3.5-Flash, with 1M tokens against 262K.

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

37 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 Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next