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DeepSeek V4 Flash 0423 vs Qwen3.6 Plus

Updated October 21, 2026. 45 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V4 Flash 0423 Replace Qwen3.6 Plus
DeepSeek V4 Flash 0423DeepSeek
Coding
54.6
Overall
24.4
Output $/M
$0.182
13
Qwen3.6 PlusQwen
Coding
37.4
Overall
27.0
Output $/M
$1.95
32
vs boards won of 45 shared

Decision reading

Pick DeepSeek V4 Flash 0423 for coding: it scores 54.6 on the Vibe Coding Index against 37.4 for Qwen3.6 Plus.

Pick Qwen3.6 Plus when what matters is AA Coding Index or LMArena Text: coding, where it leads.

Model ADeepSeek V4 Flash 0423DeepSeek54.6/1001 independent benchmarkNo cost per solved taskModel BQwen3.6 PlusQwen37.4/1001 independent benchmark$1.19 per solved task
Shared results
45
DeepSeek V4 Flash 0423 only
3
Qwen3.6 Plus only
38
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 54.6 from 1 benchmark, Qwen3.6 Plus 37.4 from 1 benchmark.
Widest category
Coding, 8.7 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: DeepSeek V4 Flash 0423 1585 against Qwen3.6 Plus 1454, 21.8 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.182 against Qwen3.6 Plus $1.95 per million output tokens, 10.7x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M 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
CategoryDeepSeek V4 Flash 0423BarsQwen3.6 PlusTies
Coding43
Intelligence02
Reasoning03
Math02
Knowledge31
Web design08
General613
All shared boards1332
CodingLike-for-likeFour of these boards feed the Vibe Coding Index43
Coding benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 PlusLeader
LMArena WebDev15821461DeepSeek V4 Flash 0423
AA Coding Index52.054.5Qwen3.6 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
Terminal-Bench Hard (Artificial Analysis run)Not measured43.9%Only Qwen3.6 Plus measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2670.1DeepSeek V4 Flash 0423
LMArena Text: coding14571467Qwen3.6 Plus
LMArena Text: software and IT14531462Qwen3.6 Plus
LMArena WebDev: React15851454DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581463DeepSeek V4 Flash 0423
LMArena WebDev: from an imageNot measured1472Only Qwen3.6 Plus measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 PlusLeader
AA Intelligence Index24.427.0Qwen3.6 Plus
Epoch Capabilities Index146.1147.3Qwen3.6 Plus
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 PlusLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
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 TelecomNot measured97.7%Only Qwen3.6 Plus measured
Vending-Bench 2Not measured$5,115Only Qwen3.6 Plus measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 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)Not measured88.2%Only Qwen3.6 Plus measured
Humanity's Last Exam (Artificial Analysis run)Not measured27.8%Only Qwen3.6 Plus measured
GPQA Diamond (Epoch AI run)Not measured88.4%Only Qwen3.6 Plus measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
Chess puzzlesNot measured14.0%Only Qwen3.6 Plus measured
Mystery game puzzlesNot measured12.0%Only Qwen3.6 Plus measured
LMArena Text: hard prompts14441448Qwen3.6 Plus
LMArena Text: expert14411454Qwen3.6 Plus
LMArena Text: hard prompts in English14491455Qwen3.6 Plus
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 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: math14261449Qwen3.6 Plus
LMArena Text: mathematical work14321448Qwen3.6 Plus
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index31
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 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: science14461439DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481442DeepSeek V4 Flash 0423
LMArena Text: legal and government14391437DeepSeek V4 Flash 0423
LMArena Text: business and finance14251430Qwen3.6 Plus
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 PlusLeader
Design Arena: websites12081243Qwen3.6 Plus
Design Arena: UI components11641233Qwen3.6 Plus
Design Arena: game dev11971211Qwen3.6 Plus
Design Arena: data viz11271228Qwen3.6 Plus
Design Arena: 3D11891202Qwen3.6 Plus
Design Arena: all code categories12051236Qwen3.6 Plus
Design Arena: SVG11551160Qwen3.6 Plus
Design Arena: ASCII art11091115Qwen3.6 Plus
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index613
General benchmarks for DeepSeek V4 Flash 0423 and Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 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
IFBenchNot measured75.2%Only Qwen3.6 Plus measured
Long context reasoning (AA-LCR)Not measured78.3%Only Qwen3.6 Plus measured
DTBench86.4%81.9%DeepSeek V4 Flash 0423
LMCA35.9%33.1%DeepSeek V4 Flash 0423
CL-benchNot measured20.3%Only Qwen3.6 Plus measured
LMArena Text14321436Qwen3.6 Plus
LMArena Text: instruction following14211424Qwen3.6 Plus
LMArena Text: creative writing14031404Qwen3.6 Plus
LMArena Text: English14411445Qwen3.6 Plus
LMArena Text: non-English14191424Qwen3.6 Plus
LMArena Text: Chinese14631477Qwen3.6 Plus
LMArena Text: German14191451Qwen3.6 Plus
LMArena Text: Japanese13891390Qwen3.6 Plus
LMArena Text: Korean13831379DeepSeek V4 Flash 0423
LMArena Text: French14391455Qwen3.6 Plus
LMArena Text: Spanish14361432DeepSeek V4 Flash 0423
LMArena Text: Russian14271434Qwen3.6 Plus
LMArena Text: Polish14361433DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491438DeepSeek V4 Flash 0423
LMArena Text: longer queries14341439Qwen3.6 Plus
LMArena Text: writing and language14101418Qwen3.6 Plus
LMArena Text: entertainment and media14001402Qwen3.6 Plus
Neither model has a result on the other 21 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 Qwen3.6 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.6 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

DeepSeek V4 Flash 0423$0.0002Fits in one request
Qwen3.6 Plus$0.0013Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0051Fits in one request
Qwen3.6 Plus$0.022Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.020Fits in one request
Qwen3.6 Plus$0.085Fits 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 Qwen3.6 Plus
SpecificationDeepSeek V4 Flash 0423Qwen3.6 Plus
MakerDeepSeekQwen
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026April 2, 2026
Context window1.05M1M
Input $/Mtok$0.091$0.325
Output $/Mtok$0.182$1.95
Coding index54.637.4
Independent measurements behind it11
Cost per solved taskNot computable$1.19
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Qwen3.6 Plus for coding?

Pick DeepSeek V4 Flash 0423 for coding: it scores 54.6 on the Vibe Coding Index against 37.4 for Qwen3.6 Plus. Pick Qwen3.6 Plus when what matters is AA Coding Index or LMArena Text: coding, where it leads.

Which is cheaper, DeepSeek V4 Flash 0423 or Qwen3.6 Plus?

DeepSeek V4 Flash 0423 costs $0.091 per million input tokens and $0.182 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, DeepSeek V4 Flash 0423 or Qwen3.6 Plus?

DeepSeek V4 Flash 0423, with 1.05M tokens against 1M.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Qwen3.6 Plus comparison based on?

45 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and Qwen3.6 Plus's on 1. Where only one model has a result, the page says so instead of naming a winner.

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