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DeepSeek V4 Flash 0423 vs GPT-4.1

DeepSeek V4 Flash 0423 leads GPT-4.1 on the Artificial Analysis Intelligence Index, 24.4 to 12.7, and DeepSeek V4 Flash 0423 costs 28.6x less per output token ($0.28 vs $8.00 per million). Updated October 21, 2026; 42 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace GPT-4.1
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
41
GPT-4.1OpenAI
Coding
No data
Overall
36.5
Output $/M
$8.00
1
vs boards won of 42 shared

DeepSeek V4 Flash 0423 or GPT-4.1: 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 28.6x cheaper ($0.28 vs $8.00 per million) and a larger context window (1.05M against 1.05M tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGPT-4.1OpenAINot benchmarkedNo coding benchmark$0.37 per solved task
Shared results
42
DeepSeek V4 Flash 0423 only
7
GPT-4.1 only
50
Like-for-like categories
7 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, GPT-4.1 not benchmarked.
Widest category
Web design, 20.7 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: 3D: DeepSeek V4 Flash 0423 1189 against GPT-4.1 850, 42.4 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against GPT-4.1 $8.00 per million output tokens, 28.6x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GPT-4.1 1.05M.

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 0423BarsGPT-4.1Ties
Coding40
Intelligence20
Reasoning41
Math20
Knowledge40
Web design60
General190
All shared boards411
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
Aider polyglotNot measured52.4%Only GPT-4.1 measured
SWE-bench VerifiedNot measured39.6%Only GPT-4.1 measured
SWE-bench MultimodalNot measured31.1%Only GPT-4.1 measured
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveCodeBench (Vals AI)Not measured54.7%Only GPT-4.1 measured
LiveCodeBench (Artificial Analysis run)Not measured45.7%Only GPT-4.1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured13.6%Only GPT-4.1 measured
WeirdML45.6%39.0%DeepSeek V4 Flash 0423
ALE-Bench678.2558.1DeepSeek V4 Flash 0423
LMArena Text: coding14571390DeepSeek V4 Flash 0423
LMArena Text: software and IT14531391DeepSeek V4 Flash 0423
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
SciCodeNot measured4.6%Only GPT-4.1 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
AA Intelligence Index24.412.7DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1136.7DeepSeek V4 Flash 0423
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured47.1%Only GPT-4.1 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured54.0%Only GPT-4.1 measured
BrowseComp-PlusNot measured36.4%Only GPT-4.1 measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
GPQA DiamondNot measured65.4%Only GPT-4.1 measured
MMMU Pro (Vals AI)Not measured72.4%Only GPT-4.1 measured
GPQA Diamond (Artificial Analysis run)Not measured66.6%Only GPT-4.1 measured
Humanity's Last Exam (Artificial Analysis run)Not measured4.2%Only GPT-4.1 measured
GPQA Diamond (Epoch AI run)Not measured66.9%Only GPT-4.1 measured
ARC-AGINot measured5.5%Only GPT-4.1 measured
ARC-AGI-2Not measured0.4%Only GPT-4.1 measured
SimpleBench46.3%27.0%DeepSeek V4 Flash 0423
Chess puzzlesNot measured3.0%Only GPT-4.1 measured
LMArena Text: hard prompts14441384DeepSeek V4 Flash 0423
LMArena Text: expert14411364DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491393DeepSeek V4 Flash 0423
LMArena Vision: diagramsNot measured1215Only GPT-4.1 measured
LMArena Vision: homeworkNot measured1248Only GPT-4.1 measured
Kagi LLM Benchmark52.2%52.3%GPT-4.1
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
AIMENot measured39.6%Only GPT-4.1 measured
MATH 500 (Vals AI)Not measured87.2%Only GPT-4.1 measured
MGSM (Vals AI)Not measured87.7%Only GPT-4.1 measured
AA Math IndexNot measured34.7Only GPT-4.1 measured
AIME 2025 (Artificial Analysis run)Not measured34.7%Only GPT-4.1 measured
OTIS Mock AIMENot measured38.3%Only GPT-4.1 measured
FrontierMath, tiers 1 to 3Not measured6.0%Only GPT-4.1 measured
MATH level 5Not measured83.0%Only GPT-4.1 measured
LMArena Text: math14261369DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321360DeepSeek V4 Flash 0423
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
MMLU ProNot measured80.5%Only GPT-4.1 measured
LegalBench (Vals AI)Not measured83.1%Only GPT-4.1 measured
CaseLaw (Vals AI)Not measured69.9%Only GPT-4.1 measured
CorpFin (Vals AI)Not measured63.0%Only GPT-4.1 measured
TaxEval (Vals AI)Not measured75.1%Only GPT-4.1 measured
MortgageTax (Vals AI)Not measured65.9%Only GPT-4.1 measured
MedQA (Vals AI)Not measured91.2%Only GPT-4.1 measured
MMLU Pro (Artificial Analysis run)Not measured80.6%Only GPT-4.1 measured
SimpleQA VerifiedNot measured31.1%Only GPT-4.1 measured
GeoBenchNot measured72.0%Only GPT-4.1 measured
LMArena Text: science14461382DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481379DeepSeek V4 Flash 0423
LMArena Text: legal and government14391399DeepSeek V4 Flash 0423
LMArena Text: business and finance14251369DeepSeek V4 Flash 0423
FACTS Benchmark SuiteNot measured45.8%Only GPT-4.1 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
Design Arena: websites12081039DeepSeek V4 Flash 0423
Design Arena: UI components11651000DeepSeek V4 Flash 0423
Design Arena: game dev11971080DeepSeek V4 Flash 0423
Design Arena: data viz11271104DeepSeek V4 Flash 0423
Design Arena: 3D1189850DeepSeek V4 Flash 0423
Design Arena: all code categories12051026DeepSeek V4 Flash 0423
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 index190
General benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
IFBenchNot measured43.0%Only GPT-4.1 measured
Long context reasoning (AA-LCR)Not measured68.3%Only GPT-4.1 measured
DTBench86.4%68.3%DeepSeek V4 Flash 0423
LMCA35.9%25.6%DeepSeek V4 Flash 0423
Fiction.LiveBenchNot measured63.9%Only GPT-4.1 measured
LMArena Text14321383DeepSeek V4 Flash 0423
LMArena Text: instruction following14211367DeepSeek V4 Flash 0423
LMArena Text: creative writing14031363DeepSeek V4 Flash 0423
LMArena VisionNot measured1210Only GPT-4.1 measured
LMArena Text: English14411392DeepSeek V4 Flash 0423
LMArena Text: non-English14191370DeepSeek V4 Flash 0423
LMArena Text: Chinese14631382DeepSeek V4 Flash 0423
LMArena Text: German14191381DeepSeek V4 Flash 0423
LMArena Text: Japanese13891319DeepSeek V4 Flash 0423
LMArena Text: Korean13831338DeepSeek V4 Flash 0423
LMArena Text: French14391382DeepSeek V4 Flash 0423
LMArena Text: Spanish14361376DeepSeek V4 Flash 0423
LMArena Text: Russian14271377DeepSeek V4 Flash 0423
LMArena Text: Polish14361389DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491397DeepSeek V4 Flash 0423
LMArena Text: longer queries14341385DeepSeek V4 Flash 0423
LMArena Text: writing and language14101371DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001365DeepSeek V4 Flash 0423
LMArena Vision: EnglishNot measured1209Only GPT-4.1 measured
LMArena Vision: ChineseNot measured1226Only GPT-4.1 measured
LMArena Vision: reading textNot measured1218Only GPT-4.1 measured
LMArena Vision: humorNot measured1196Only GPT-4.1 measured
LMArena Vision: captioningNot measured1207Only GPT-4.1 measured
LMArena Vision: recognizing thingsNot measured1208Only GPT-4.1 measured
LMArena Vision: creative writingNot measured1210Only GPT-4.1 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 GPT-4.1
BenchmarkDeepSeek V4 Flash 0423GPT-4.1Leader
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
GPT-4.1$0.0060Fits 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
GPT-4.1$0.124Fits 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
GPT-4.1$0.480Fits 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 GPT-4.1
SpecificationDeepSeek V4 Flash 0423OpenAI GPT-4.1
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026April 14, 2025
Context window1.05M1.05M
Input $/Mtok$0.13$2.00
Output $/Mtok$0.28$8.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computable$0.37
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than GPT-4.1 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 28.6x cheaper ($0.28 vs $8.00 per million) and a larger context window (1.05M against 1.05M tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or GPT-4.1?

DeepSeek V4 Flash 0423 costs $0.13 per million input tokens and $0.28 per million output tokens; GPT-4.1 costs $2.00 and $8.00. Cost per solved task is known for GPT-4.1 only.

Which has the bigger context window, DeepSeek V4 Flash 0423 or GPT-4.1?

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

How many benchmarks is the DeepSeek V4 Flash 0423 vs GPT-4.1 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 GPT-4.1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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