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DeepSeek V4 Flash 0423 vs GPT-5.3-Codex

GPT-5.3-Codex leads DeepSeek V4 Flash 0423 on the Artificial Analysis Intelligence Index, 32.5 to 24.4, and DeepSeek V4 Flash 0423 costs 50.0x less per output token ($0.28 vs $14.00 per million). Updated October 21, 2026; 15 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace GPT-5.3-Codex
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
9
GPT-5.3-CodexOpenAI
Coding
60.0
Overall
No data
Output $/M
$14.00
6
vs boards won of 15 shared

DeepSeek V4 Flash 0423 or GPT-5.3-Codex: which to pick

Only GPT-5.3-Codex has a coding score, 60.0 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 50.0x cheaper ($0.28 vs $14.00 per million) and a larger context window (1.05M against 400K tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGPT-5.3-CodexOpenAI60.0/1003 independent benchmarks$0.59 per solved task
Shared results
15
DeepSeek V4 Flash 0423 only
34
GPT-5.3-Codex only
19
Like-for-like categories
3 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-5.3-Codex 60.0 from 3 benchmarks.
Widest category
Coding, 29.1 points apart on average over 5 shared benchmarks.
Widest single gap
WeirdML: DeepSeek V4 Flash 0423 45.6% against GPT-5.3-Codex 79.3%, 33.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against GPT-5.3-Codex $14.00 per million output tokens, 50.0x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GPT-5.3-Codex 400K.

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-5.3-CodexTies
Coding32
Intelligence02
Web design62
All shared boards96
CodingLike-for-likeSix of these boards feed the Vibe Coding Index32
Coding benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
LMArena WebDev15821407DeepSeek V4 Flash 0423
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveCodeBench (Vals AI)Not measured87.3%Only GPT-5.3-Codex measured
SWE-bench Verified (Vals AI)Not measured78.0%Only GPT-5.3-Codex measured
Vibe Code Bench (Vals AI)Not measured61.8%Only GPT-5.3-Codex measured
IOI (Vals AI)Not measured53.8%Only GPT-5.3-Codex measured
Terminal-Bench Hard (Artificial Analysis run)Not measured53.0%Only GPT-5.3-Codex measured
Terminal-BenchNot measured78.4%Only GPT-5.3-Codex measured
WeirdML45.6%79.3%GPT-5.3-Codex
ALE-Bench678.21655.2GPT-5.3-Codex
LMArena Text: coding1457Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: software and IT1453Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: React15851395DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581422DeepSeek V4 Flash 0423
LMArena WebDev: from an imageNot measured1443Only GPT-5.3-Codex 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 GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
AA Intelligence Index24.432.5GPT-5.3-Codex
Epoch Capabilities Index146.1157.1GPT-5.3-Codex
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: agents building web appsNot measured1032Only GPT-5.3-Codex measured
Design Arena: agents building full-stack appsNot measured983Only GPT-5.3-Codex measured
Design Arena: agents building mobile appsNot measured1054Only GPT-5.3-Codex measured
Design Arena: agents building Android appsNot measured1084Only GPT-5.3-Codex measured
Design Arena: agents building Godot gamesNot measured1124Only GPT-5.3-Codex measured
τ²-Bench TelecomNot measured86.0%Only GPT-5.3-Codex measured
METR time horizonsNot measured74.5%Only GPT-5.3-Codex measured
Vending-Bench 2Not measured$5,940Only GPT-5.3-Codex measured
Neither model has a result on the other 32 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
GPQA Diamond (Artificial Analysis run)Not measured91.5%Only GPT-5.3-Codex measured
Humanity's Last Exam (Artificial Analysis run)Not measured42.5%Only GPT-5.3-Codex measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts1444Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: expert1441Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts in English1449Not measuredOnly DeepSeek V4 Flash 0423 measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Math benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
LMArena Text: math1426Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: mathematical work1432Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
LMArena Text: science1446Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: medicine and healthcare1448Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: legal and government1439Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: business and finance1425Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 14 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index62
Web design benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
Design Arena: websites12081163DeepSeek V4 Flash 0423
Design Arena: UI components11651137DeepSeek V4 Flash 0423
Design Arena: game dev11971161DeepSeek V4 Flash 0423
Design Arena: data viz11271164GPT-5.3-Codex
Design Arena: 3D11891008DeepSeek V4 Flash 0423
Design Arena: all code categories12051145DeepSeek V4 Flash 0423
Design Arena: SVG11551129DeepSeek V4 Flash 0423
Design Arena: ASCII art11091152GPT-5.3-Codex
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards, none shared
General benchmarks for DeepSeek V4 Flash 0423 and GPT-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
IFBenchNot measured75.4%Only GPT-5.3-Codex measured
Long context reasoning (AA-LCR)Not measured83.3%Only GPT-5.3-Codex measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text1432Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: instruction following1421Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: creative writing1403Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: English1441Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: non-English1419Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Chinese1463Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: German1419Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Japanese1389Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Korean1383Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: French1439Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Spanish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Russian1427Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Polish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: multi-turn1449Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: longer queries1434Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: writing and language1410Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: entertainment and media1400Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 25 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-5.3-Codex
BenchmarkDeepSeek V4 Flash 0423GPT-5.3-CodexLeader
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-5.3-Codex$0.0088Fits 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-5.3-Codex$0.130Fits 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-5.3-Codex$0.490Fits 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-5.3-Codex
SpecificationDeepSeek V4 Flash 0423OpenAI GPT-5.3-Codex
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026February 24, 2026
Context window1.05M400K
Input $/Mtok$0.13$1.75
Output $/Mtok$0.28$14.00
Coding indexNot benchmarked60.0
Independent measurements behind it13
Cost per solved taskNot computable$0.59
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than GPT-5.3-Codex for coding?

Only GPT-5.3-Codex has a coding score, 60.0 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 50.0x cheaper ($0.28 vs $14.00 per million) and a larger context window (1.05M against 400K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or GPT-5.3-Codex?

DeepSeek V4 Flash 0423 costs $0.13 per million input tokens and $0.28 per million output tokens; GPT-5.3-Codex costs $1.75 and $14.00. Cost per solved task is known for GPT-5.3-Codex only.

Which has the bigger context window, DeepSeek V4 Flash 0423 or GPT-5.3-Codex?

DeepSeek V4 Flash 0423, with 1.05M tokens against 400K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs GPT-5.3-Codex comparison based on?

15 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-5.3-Codex's on 3. Where only one model has a result, the page says so instead of naming a winner.

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