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DeepSeek V4 Flash 0423 vs GPT-4.1 Mini

Updated October 21, 2026. 40 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 GPT-4.1 Mini
DeepSeek V4 Flash 0423DeepSeek
Coding
54.6
Overall
24.4
Output $/M
$0.182
40
GPT-4.1 MiniOpenAI
Coding
28.5
Overall
10.2
Output $/M
$1.60
0
vs boards won of 40 shared

Decision reading

Pick DeepSeek V4 Flash 0423 for coding: it scores 54.6 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini, though on 1 benchmark against 2.

GPT-4.1 Mini is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Model ADeepSeek V4 Flash 0423DeepSeek54.6/1001 independent benchmarkNo cost per solved taskModel BGPT-4.1 MiniOpenAI28.5/1002 independent benchmarks$1.818 per solved task
Shared results
40
DeepSeek V4 Flash 0423 only
8
GPT-4.1 Mini only
44
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, GPT-4.1 Mini 28.5 from 2 benchmarks.
Widest category
Web design, 24.9 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: 3D: DeepSeek V4 Flash 0423 1189 against GPT-4.1 Mini 837, 44.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.182 against GPT-4.1 Mini $1.60 per million output tokens, 8.8x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GPT-4.1 Mini 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-4.1 MiniTies
Coding40
Intelligence20
Reasoning30
Math20
Knowledge40
Web design60
General190
All shared boards400
CodingLike-for-likeFour of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
Aider polyglotNot measured32.4%Only GPT-4.1 Mini measured
SWE-bench VerifiedNot measured23.9%Only GPT-4.1 Mini measured
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.020.2DeepSeek V4 Flash 0423
LiveCodeBench (Vals AI)Not measured58.2%Only GPT-4.1 Mini measured
LiveCodeBench (Artificial Analysis run)Not measured48.3%Only GPT-4.1 Mini measured
Terminal-Bench Hard (Artificial Analysis run)Not measured7.6%Only GPT-4.1 Mini measured
WeirdML45.6%37.6%DeepSeek V4 Flash 0423
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571367DeepSeek V4 Flash 0423
LMArena Text: software and IT14531360DeepSeek V4 Flash 0423
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 25 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 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
AA Intelligence Index24.410.2DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1134.9DeepSeek V4 Flash 0423
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
τ²-Bench TelecomNot measured52.9%Only GPT-4.1 Mini measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GPT-4.1 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
GPQA DiamondNot measured67.9%Only GPT-4.1 Mini measured
MMMU Pro (Vals AI)Not measured70.5%Only GPT-4.1 Mini measured
GPQA Diamond (Artificial Analysis run)Not measured66.4%Only GPT-4.1 Mini measured
Humanity's Last Exam (Artificial Analysis run)Not measured5.0%Only GPT-4.1 Mini measured
GPQA Diamond (Epoch AI run)Not measured65.8%Only GPT-4.1 Mini measured
ARC-AGINot measured3.5%Only GPT-4.1 Mini measured
ARC-AGI-2Not measured0.0%Only GPT-4.1 Mini measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
Chess puzzlesNot measured1.0%Only GPT-4.1 Mini measured
Mystery game puzzlesNot measured7.0%Only GPT-4.1 Mini measured
LMArena Text: hard prompts14441349DeepSeek V4 Flash 0423
LMArena Text: expert14411338DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491362DeepSeek V4 Flash 0423
LMArena Vision: diagramsNot measured1182Only GPT-4.1 Mini measured
LMArena Vision: homeworkNot measured1214Only GPT-4.1 Mini measured
Neither model has a result on the other 6 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 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
AIMENot measured49.4%Only GPT-4.1 Mini measured
MATH 500 (Vals AI)Not measured88.0%Only GPT-4.1 Mini measured
MGSM (Vals AI)Not measured87.8%Only GPT-4.1 Mini measured
AA Math IndexNot measured46.3Only GPT-4.1 Mini measured
AIME 2025 (Artificial Analysis run)Not measured46.3%Only GPT-4.1 Mini measured
OTIS Mock AIMENot measured44.7%Only GPT-4.1 Mini measured
FrontierMath, tiers 1 to 3Not measured6.7%Only GPT-4.1 Mini measured
MATH level 5Not measured87.3%Only GPT-4.1 Mini measured
LMArena Text: math14261343DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321347DeepSeek 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 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
MMLU ProNot measured77.2%Only GPT-4.1 Mini measured
LegalBench (Vals AI)Not measured78.0%Only GPT-4.1 Mini measured
CorpFin (Vals AI)Not measured57.9%Only GPT-4.1 Mini measured
TaxEval (Vals AI)Not measured71.9%Only GPT-4.1 Mini measured
MortgageTax (Vals AI)Not measured65.5%Only GPT-4.1 Mini measured
MedQA (Vals AI)Not measured84.6%Only GPT-4.1 Mini measured
MMLU Pro (Artificial Analysis run)Not measured78.1%Only GPT-4.1 Mini measured
SimpleQA VerifiedNot measured12.7%Only GPT-4.1 Mini measured
LMArena Text: science14461328DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481324DeepSeek V4 Flash 0423
LMArena Text: legal and government14391343DeepSeek V4 Flash 0423
LMArena Text: business and finance14251322DeepSeek V4 Flash 0423
Neither model has a result on the other 5 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 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
Design Arena: websites1208997DeepSeek V4 Flash 0423
Design Arena: UI components1164961DeepSeek V4 Flash 0423
Design Arena: game dev11971071DeepSeek V4 Flash 0423
Design Arena: data viz11271034DeepSeek V4 Flash 0423
Design Arena: 3D1189837DeepSeek V4 Flash 0423
Design Arena: all code categories1205994DeepSeek 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 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
IFBenchNot measured38.3%Only GPT-4.1 Mini measured
Long context reasoning (AA-LCR)Not measured44.0%Only GPT-4.1 Mini measured
DTBench86.4%68.8%DeepSeek V4 Flash 0423
LMCA35.9%21.1%DeepSeek V4 Flash 0423
Fiction.LiveBenchNot measured44.4%Only GPT-4.1 Mini measured
LMArena Text14321341DeepSeek V4 Flash 0423
LMArena Text: instruction following14211333DeepSeek V4 Flash 0423
LMArena Text: creative writing14031299DeepSeek V4 Flash 0423
LMArena VisionNot measured1181Only GPT-4.1 Mini measured
LMArena Text: English14411356DeepSeek V4 Flash 0423
LMArena Text: non-English14191318DeepSeek V4 Flash 0423
LMArena Text: Chinese14631329DeepSeek V4 Flash 0423
LMArena Text: German14191350DeepSeek V4 Flash 0423
LMArena Text: Japanese13891290DeepSeek V4 Flash 0423
LMArena Text: Korean13831298DeepSeek V4 Flash 0423
LMArena Text: French14391358DeepSeek V4 Flash 0423
LMArena Text: Spanish14361319DeepSeek V4 Flash 0423
LMArena Text: Russian14271324DeepSeek V4 Flash 0423
LMArena Text: Polish14361326DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491354DeepSeek V4 Flash 0423
LMArena Text: longer queries14341344DeepSeek V4 Flash 0423
LMArena Text: writing and language14101319DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001300DeepSeek V4 Flash 0423
LMArena Vision: EnglishNot measured1191Only GPT-4.1 Mini measured
LMArena Vision: ChineseNot measured1186Only GPT-4.1 Mini measured
LMArena Vision: reading textNot measured1188Only GPT-4.1 Mini measured
LMArena Vision: humorNot measured1182Only GPT-4.1 Mini measured
LMArena Vision: captioningNot measured1174Only GPT-4.1 Mini measured
LMArena Vision: recognizing thingsNot measured1187Only GPT-4.1 Mini measured
LMArena Vision: creative writingNot measured1182Only GPT-4.1 Mini 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 Mini
BenchmarkDeepSeek V4 Flash 0423GPT-4.1 MiniLeader
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
GPT-4.1 Mini$0.0012Fits 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
GPT-4.1 Mini$0.025Fits 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
GPT-4.1 Mini$0.096Fits 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 Mini
SpecificationDeepSeek V4 Flash 0423OpenAI GPT-4.1 Mini
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026April 14, 2025
Context window1.05M1.05M
Input $/Mtok$0.091$0.40
Output $/Mtok$0.182$1.60
Coding index54.628.5
Independent measurements behind it12
Cost per solved taskNot computable$1.818
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than GPT-4.1 Mini for coding?

Pick DeepSeek V4 Flash 0423 for coding: it scores 54.6 on the Vibe Coding Index against 28.5 for GPT-4.1 Mini, though on 1 benchmark against 2. GPT-4.1 Mini is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

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

DeepSeek V4 Flash 0423 costs $0.091 per million input tokens and $0.182 per million output tokens; GPT-4.1 Mini costs $0.40 and $1.60. Cost per solved task is known for GPT-4.1 Mini only.

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

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

How many benchmarks is the DeepSeek V4 Flash 0423 vs GPT-4.1 Mini comparison based on?

40 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 Mini's on 2. Where only one model has a result, the page says so instead of naming a winner.

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