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DeepSeek V4 Flash 0423 vs Qwen3.7 Plus

Qwen3.7 Plus leads DeepSeek V4 Flash 0423 on the Artificial Analysis Intelligence Index, 25.2 to 24.4, and DeepSeek V4 Flash 0423 costs 4.6x less per output token ($0.28 vs $1.28 per million). Updated October 21, 2026; 42 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace Qwen3.7 Plus
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
2
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
40
vs boards won of 42 shared

DeepSeek V4 Flash 0423 or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash 0423 for output tokens 4.6x cheaper ($0.28 vs $1.28 per million) and a larger context window (1.05M against 1M tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
42
DeepSeek V4 Flash 0423 only
7
Qwen3.7 Plus only
33
Like-for-like categories
8 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, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Web design, 8.9 points apart on average over 8 shared benchmarks.
Widest single gap
Design Arena: data viz: DeepSeek V4 Flash 0423 1127 against Qwen3.7 Plus 1276, 18.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Qwen3.7 Plus $1.28 per million output tokens, 4.6x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, Qwen3.7 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 0423BarsQwen3.7 PlusTies
Coding03
Intelligence02
Agentic work10
Reasoning03
Math02
Knowledge04
Web design08
General118
All shared boards240
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.055.9Qwen3.7 Plus
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
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571473Qwen3.7 Plus
LMArena Text: software and IT14531473Qwen3.7 Plus
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
AA Intelligence Index24.425.2Qwen3.7 Plus
Epoch Capabilities Index146.1147.0Qwen3.7 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
AA Agentic Index26.317.5DeepSeek V4 Flash 0423
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 index03
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
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)Not measured87.9%Only Qwen3.7 Plus measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts14441460Qwen3.7 Plus
LMArena Text: expert14411466Qwen3.7 Plus
LMArena Text: hard prompts in English14491460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
OTIS Mock AIMENot measured93.3%Only Qwen3.7 Plus measured
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
LMArena Text: math14261467Qwen3.7 Plus
LMArena Text: mathematical work14321470Qwen3.7 Plus
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
LMArena Text: science14461464Qwen3.7 Plus
LMArena Text: medicine and healthcare14481464Qwen3.7 Plus
LMArena Text: legal and government14391451Qwen3.7 Plus
LMArena Text: business and finance14251435Qwen3.7 Plus
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
Design Arena: websites12081269Qwen3.7 Plus
Design Arena: UI components11651261Qwen3.7 Plus
Design Arena: game dev11971262Qwen3.7 Plus
Design Arena: data viz11271276Qwen3.7 Plus
Design Arena: 3D11891239Qwen3.7 Plus
Design Arena: all code categories12051269Qwen3.7 Plus
Design Arena: SVG11551208Qwen3.7 Plus
Design Arena: ASCII art11091143Qwen3.7 Plus
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index118
General benchmarks for DeepSeek V4 Flash 0423 and Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus 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
DTBench86.4%84.0%DeepSeek V4 Flash 0423
LMCA35.9%37.6%Qwen3.7 Plus
LMArena Text14321454Qwen3.7 Plus
LMArena Text: instruction following14211439Qwen3.7 Plus
LMArena Text: creative writing14031438Qwen3.7 Plus
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: English14411458Qwen3.7 Plus
LMArena Text: non-English14191445Qwen3.7 Plus
LMArena Text: Chinese14631509Qwen3.7 Plus
LMArena Text: German14191471Qwen3.7 Plus
LMArena Text: Japanese13891412Qwen3.7 Plus
LMArena Text: Korean13831413Qwen3.7 Plus
LMArena Text: French14391472Qwen3.7 Plus
LMArena Text: Spanish14361457Qwen3.7 Plus
LMArena Text: Russian14271457Qwen3.7 Plus
LMArena Text: Polish14361449Qwen3.7 Plus
LMArena Text: multi-turn14491459Qwen3.7 Plus
LMArena Text: longer queries14341454Qwen3.7 Plus
LMArena Text: writing and language14101437Qwen3.7 Plus
LMArena Text: entertainment and media14001422Qwen3.7 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 16 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 Qwen3.7 Plus
BenchmarkDeepSeek V4 Flash 0423Qwen3.7 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

DeepSeek V4 Flash 0423$0.0003Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0073Fits in one request
Qwen3.7 Plus$0.020Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.029Fits in one request
Qwen3.7 Plus$0.077Fits 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 Qwen3.7 Plus
SpecificationDeepSeek V4 Flash 0423Qwen3.7 Plus
MakerDeepSeekQwen
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026June 3, 2026
Context window1.05M1M
Input $/Mtok$0.13$0.32
Output $/Mtok$0.28$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it12
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 4.6x cheaper ($0.28 vs $1.28 per million) and a larger context window (1.05M against 1M tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or Qwen3.7 Plus?

DeepSeek V4 Flash 0423 costs $0.13 per million input tokens and $0.28 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Qwen3.7 Plus?

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

How many benchmarks is the DeepSeek V4 Flash 0423 vs Qwen3.7 Plus comparison based on?

42 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 Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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