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DeepSeek V4 Flash 0423 vs Qwen3.5-27B

DeepSeek V4 Flash 0423 leads Qwen3.5-27B on the Artificial Analysis Intelligence Index, 24.4 to 22.9, and DeepSeek V4 Flash 0423 costs 5.6x less per output token ($0.28 vs $1.56 per million). Updated October 22, 2026; 36 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace Qwen3.5-27B
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
34
Qwen3.5-27BQwen
Coding
No data
Overall
No data
Output $/M
$1.56
2
vs boards won of 36 shared

DeepSeek V4 Flash 0423 or Qwen3.5-27B: which to pick

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

Pick DeepSeek V4 Flash 0423 for output tokens 5.6x cheaper ($0.28 vs $1.56 per million) and a larger context window (1.05M against 262K tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.5-27BQwenNot benchmarked1 independent benchmarkNo cost per solved task
Shared results
36
DeepSeek V4 Flash 0423 only
13
Qwen3.5-27B only
17
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
DeepSeek V4 Flash 0423 not benchmarked, Qwen3.5-27B not benchmarked.
Widest category
Coding, 18.0 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: DeepSeek V4 Flash 0423 1585 against Qwen3.5-27B 1346, 39.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Qwen3.5-27B $1.56 per million output tokens, 5.6x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, Qwen3.5-27B 262K.

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
CategoryDeepSeek V4 Flash 0423BarsQwen3.5-27BTies
Coding70
Intelligence10
Reasoning30
Math11
Knowledge40
General181
All shared boards342
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
LMArena WebDev15821358DeepSeek V4 Flash 0423
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured32.6%Only Qwen3.5-27B measured
WeirdML45.6%39.5%DeepSeek V4 Flash 0423
ALE-Bench678.2349.4DeepSeek V4 Flash 0423
LMArena Text: coding14571427DeepSeek V4 Flash 0423
LMArena Text: software and IT14531431DeepSeek V4 Flash 0423
LMArena WebDev: React15851346DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581386DeepSeek V4 Flash 0423
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
AA Intelligence Index24.422.9DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1Not measuredOnly DeepSeek V4 Flash 0423 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured93.9%Only Qwen3.5-27B measured
Vending-Bench 2Not measured$202Only Qwen3.5-27B measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
GPQA Diamond (Artificial Analysis run)Not measured85.8%Only Qwen3.5-27B measured
Humanity's Last Exam (Artificial Analysis run)Not measured23.9%Only Qwen3.5-27B measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441415DeepSeek V4 Flash 0423
LMArena Text: expert14411427DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491429DeepSeek V4 Flash 0423
LMArena Vision: diagramsNot measured1249Only Qwen3.5-27B measured
LMArena Vision: homeworkNot measured1256Only Qwen3.5-27B measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index11
Math benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
LMArena Text: math14261429Qwen3.5-27B
LMArena Text: mathematical work14321429DeepSeek V4 Flash 0423
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
LMArena Text: science14461437DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481425DeepSeek V4 Flash 0423
LMArena Text: legal and government14391405DeepSeek V4 Flash 0423
LMArena Text: business and finance14251399DeepSeek V4 Flash 0423
Neither model has a result on the other 14 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
Design Arena: websites1207Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: UI components1162Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: game dev1196Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: data viz1127Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: 3D1188Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: all code categories1205Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: SVG1155Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index181
General benchmarks for DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
IFBenchNot measured75.6%Only Qwen3.5-27B measured
Long context reasoning (AA-LCR)Not measured77.7%Only Qwen3.5-27B measured
DTBench86.4%82.4%DeepSeek V4 Flash 0423
LMCA35.9%34.0%DeepSeek V4 Flash 0423
LMArena Text14321409DeepSeek V4 Flash 0423
LMArena Text: instruction following14211393DeepSeek V4 Flash 0423
LMArena Text: creative writing14031362DeepSeek V4 Flash 0423
LMArena VisionNot measured1241Only Qwen3.5-27B measured
LMArena Text: English14411425DeepSeek V4 Flash 0423
LMArena Text: non-English14191390DeepSeek V4 Flash 0423
LMArena Text: Chinese14631478Qwen3.5-27B
LMArena Text: German14191392DeepSeek V4 Flash 0423
LMArena Text: Japanese13891346DeepSeek V4 Flash 0423
LMArena Text: Korean13831359DeepSeek V4 Flash 0423
LMArena Text: French14391410DeepSeek V4 Flash 0423
LMArena Text: Spanish14361407DeepSeek V4 Flash 0423
LMArena Text: Russian14271390DeepSeek V4 Flash 0423
LMArena Text: Polish14361375DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491410DeepSeek V4 Flash 0423
LMArena Text: longer queries14341413DeepSeek V4 Flash 0423
LMArena Text: writing and language14101380DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001363DeepSeek V4 Flash 0423
LMArena Vision: EnglishNot measured1246Only Qwen3.5-27B measured
LMArena Vision: ChineseNot measured1301Only Qwen3.5-27B measured
LMArena Vision: reading textNot measured1246Only Qwen3.5-27B measured
LMArena Vision: humorNot measured1227Only Qwen3.5-27B measured
LMArena Vision: captioningNot measured1170Only Qwen3.5-27B measured
LMArena Vision: recognizing thingsNot measured1210Only Qwen3.5-27B measured
LMArena Vision: creative writingNot measured1224Only Qwen3.5-27B 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 DeepSeek V4 Flash 0423 and Qwen3.5-27B
BenchmarkDeepSeek V4 Flash 0423Qwen3.5-27BLeader
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

DeepSeek V4 Flash 0423$0.0003Fits in one request
Qwen3.5-27B$0.0010Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
Qwen3.5-27B$0.014Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
Qwen3.5-27B$0.055Fits in one request

DeepSeek V4 Flash 0423 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 DeepSeek V4 Flash 0423 and Qwen3.5-27B
SpecificationDeepSeek V4 Flash 0423Qwen3.5-27B
MakerDeepSeekQwen
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026February 25, 2026
Context window1.05M262K
Input $/Mtok$0.14$0.195
Output $/Mtok$0.28$1.56
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it11
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Qwen3.5-27B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 5.6x cheaper ($0.28 vs $1.56 per million) and a larger context window (1.05M against 262K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or Qwen3.5-27B?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; Qwen3.5-27B costs $0.195 and $1.56. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Qwen3.5-27B?

DeepSeek V4 Flash 0423, with 1.05M tokens against 262K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Qwen3.5-27B comparison based on?

36 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and Qwen3.5-27B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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