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Qwen3.5-Flash vs Qwen3.7 Plus

Qwen3.5-Flash leads Qwen3.7 Plus on coding, 41.1 to 33.2 on the Vibe Coding Index, and Qwen3.5-Flash costs 4.9x less per output token ($0.26 vs $1.28 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace Qwen3.5-Flash Replace Qwen3.7 Plus
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
3
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
34
vs boards won of 37 shared

Qwen3.5-Flash or Qwen3.7 Plus: which to pick

Pick Qwen3.5-Flash for coding: it scores 41.1 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus.

Pick Qwen3.7 Plus for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
37
Qwen3.5-Flash only
18
Qwen3.7 Plus only
38
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-Flash 41.1 from 2 benchmarks, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Math, 11.1 points apart on average over 4 shared benchmarks.
Widest single gap
FrontierMath, tiers 1 to 3: Qwen3.5-Flash 18.2% against Qwen3.7 Plus 34.4%, 16.1 points apart on a 0 to 100 scale.
Output price
Qwen3.5-Flash $0.26 against Qwen3.7 Plus $1.28 per million output tokens, 4.9x apart.
Context window
Both take 1M 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-FlashBarsQwen3.7 PlusTies
Coding02
Intelligence01
Reasoning14
Math04
Knowledge14
General119
All shared boards334
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
LMArena WebDev1244Not measuredOnly Qwen3.5-Flash measured
AA Coding IndexNot measured55.9Only Qwen3.7 Plus measured
LiveCodeBench (Vals AI)83.3%Not measuredOnly Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)64.4%Not measuredOnly Qwen3.5-Flash measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
SciCodeNot measured46.1%Only Qwen3.7 Plus measured
Terminal-Bench Hard (Artificial Analysis run)Not measured47.0%Only Qwen3.7 Plus measured
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
ALE-Bench265.9Not measuredOnly Qwen3.5-Flash measured
LMArena Text: coding14121473Qwen3.7 Plus
LMArena Text: software and IT14161473Qwen3.7 Plus
LMArena WebDev: React1229Not measuredOnly Qwen3.5-Flash measured
LMArena WebDev: HTML1291Not measuredOnly Qwen3.5-Flash measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
AA Intelligence IndexNot measured25.2Only Qwen3.7 Plus measured
Epoch Capabilities Index143.5147.0Qwen3.7 Plus
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
AA Agentic IndexNot measured17.5Only Qwen3.7 Plus measured
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench TelecomNot measured93.0%Only Qwen3.7 Plus measured
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index14
Reasoning benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
GPQA Diamond82.8%Not measuredOnly Qwen3.5-Flash measured
MMMU Pro (Vals AI)81.9%Not measuredOnly Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)Not measured90.0%Only Qwen3.7 Plus measured
Humanity's Last Exam (Artificial Analysis run)Not measured35.6%Only Qwen3.7 Plus measured
GPQA Diamond (Epoch AI run)82.3%87.9%Qwen3.7 Plus
Chess puzzles14.0%Not measuredOnly Qwen3.5-Flash measured
Mystery game puzzles20.0%17.0%Qwen3.5-Flash
LMArena Text: hard prompts14031460Qwen3.7 Plus
LMArena Text: expert14071466Qwen3.7 Plus
LMArena Text: hard prompts in English14091460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
AIME92.5%Not measuredOnly Qwen3.5-Flash measured
OTIS Mock AIME84.4%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 318.2%34.4%Qwen3.7 Plus
LMArena Text: math14071467Qwen3.7 Plus
LMArena Text: mathematical work14131470Qwen3.7 Plus
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
MMLU Pro84.1%Not measuredOnly Qwen3.5-Flash measured
LegalBench (Vals AI)84.3%Not measuredOnly Qwen3.5-Flash measured
CaseLaw (Vals AI)56.0%Not measuredOnly Qwen3.5-Flash measured
CorpFin (Vals AI)63.6%Not measuredOnly Qwen3.5-Flash measured
TaxEval (Vals AI)72.2%Not measuredOnly Qwen3.5-Flash measured
MortgageTax (Vals AI)67.4%66.2%Qwen3.5-Flash
MedCode (Vals AI)33.0%Not measuredOnly Qwen3.5-Flash measured
SimpleQA Verified20.3%Not measuredOnly Qwen3.5-Flash measured
LMArena Text: science14151464Qwen3.7 Plus
LMArena Text: medicine and healthcare14071464Qwen3.7 Plus
LMArena Text: legal and government13981451Qwen3.7 Plus
LMArena Text: business and finance13941435Qwen3.7 Plus
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
Design Arena: websitesNot measured1269Only Qwen3.7 Plus measured
Design Arena: UI componentsNot measured1258Only Qwen3.7 Plus measured
Design Arena: game devNot measured1262Only Qwen3.7 Plus measured
Design Arena: data vizNot measured1277Only Qwen3.7 Plus measured
Design Arena: 3DNot measured1238Only Qwen3.7 Plus measured
Design Arena: all code categoriesNot measured1268Only Qwen3.7 Plus measured
Design Arena: SVGNot measured1207Only Qwen3.7 Plus measured
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index119
General benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 PlusLeader
SAGE (Vals AI)42.5%39.3%Qwen3.5-Flash
MedScribe (Vals AI)70.6%Not measuredOnly Qwen3.5-Flash measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBenchNot measured78.0%Only Qwen3.7 Plus measured
Long context reasoning (AA-LCR)Not measured73.0%Only Qwen3.7 Plus measured
DTBench82.9%84.0%Qwen3.7 Plus
LMCA29.1%37.6%Qwen3.7 Plus
LMArena Text13971454Qwen3.7 Plus
LMArena Text: instruction following13741439Qwen3.7 Plus
LMArena Text: creative writing13431438Qwen3.7 Plus
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: English14041458Qwen3.7 Plus
LMArena Text: non-English13851445Qwen3.7 Plus
LMArena Text: Chinese14451509Qwen3.7 Plus
LMArena Text: German13901471Qwen3.7 Plus
LMArena Text: Japanese13691412Qwen3.7 Plus
LMArena Text: Korean13441413Qwen3.7 Plus
LMArena Text: French14131472Qwen3.7 Plus
LMArena Text: Spanish14001457Qwen3.7 Plus
LMArena Text: Russian13801457Qwen3.7 Plus
LMArena Text: Polish13761449Qwen3.7 Plus
LMArena Text: multi-turn13931459Qwen3.7 Plus
LMArena Text: longer queries13921454Qwen3.7 Plus
LMArena Text: writing and language13691437Qwen3.7 Plus
LMArena Text: entertainment and media13471422Qwen3.7 Plus
LMArena Vision: EnglishNot measured1280Only Qwen3.7 Plus measured
LMArena Vision: ChineseNot measured1332Only Qwen3.7 Plus measured
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen3.5-Flash and Qwen3.7 Plus
BenchmarkQwen3.5-FlashQwen3.7 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-Flash$0.0002Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

Qwen3.5-Flash$0.0040Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Qwen3.5-Flash$0.016Fits in one request
Qwen3.7 Plus$0.077Fits 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-Flash and Qwen3.7 Plus
SpecificationQwen3.5-FlashQwen3.7 Plus
MakerQwenQwen
WeightsNo public weights listedNo public weights listed
ReleasedFebruary 25, 2026June 3, 2026
Context window1M1M
Input $/Mtok$0.065$0.32
Output $/Mtok$0.26$1.28
Coding index41.133.2
Independent measurements behind it22
Cost per solved task$0.40Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3.5-Flash better than Qwen3.7 Plus for coding?

Pick Qwen3.5-Flash for coding: it scores 41.1 on the Vibe Coding Index against 33.2 for Qwen3.7 Plus. Pick Qwen3.7 Plus for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Qwen3.5-Flash or Qwen3.7 Plus?

Qwen3.5-Flash costs $0.065 per million input tokens and $0.26 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for Qwen3.5-Flash only.

Which has the bigger context window, Qwen3.5-Flash or Qwen3.7 Plus?

Neither: both take 1M tokens.

How many benchmarks is the Qwen3.5-Flash vs Qwen3.7 Plus comparison based on?

37 benchmarks have a result for both models as of October 22, 2026. Qwen3.5-Flash's coding index rests on 2 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/qwen3-5-flash-02-23-vs-qwen3-7-plus" title="Qwen3.5-Flash vs Qwen3.7 Plus, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/qwen3-5-flash-02-23-vs-qwen3-7-plus">LLMBenchmark.ai, Qwen3.5-Flash vs Qwen3.7 Plus</a></p>