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DeepSeek V4 Flash 0423 vs GPT-6.1 Sol

GPT-6.1 Sol leads DeepSeek V4 Flash 0423 on the Artificial Analysis Intelligence Index, 51.8 to 24.4, and DeepSeek V4 Flash 0423 costs 35.7x less per output token ($0.28 vs $10.00 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace GPT-6.1 Sol
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
3
GPT-6.1 SolOpenAI
Coding
82.4
Overall
81.4
Output $/M
$10.00
35
vs boards won of 38 shared

DeepSeek V4 Flash 0423 or GPT-6.1 Sol: which to pick

Only GPT-6.1 Sol has a coding score, 82.4 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 35.7x cheaper ($0.28 vs $10.00 per million) and work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGPT-6.1 SolOpenAI82.4/1005 independent benchmarksNo cost per solved task
Shared results
38
DeepSeek V4 Flash 0423 only
11
GPT-6.1 Sol only
60
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-6.1 Sol 82.4 from 5 benchmarks.
Widest category
Intelligence, 27.6 points apart on average over 2 shared benchmarks.
Widest single gap
ALE-Bench: DeepSeek V4 Flash 0423 678.2 against GPT-6.1 Sol 2743.8, 68.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against GPT-6.1 Sol $10.00 per million output tokens, 35.7x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, GPT-6.1 Sol 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-6.1 SolTies
Coding06
Intelligence02
Reasoning03
Math02
Knowledge22
Web design06
General114
All shared boards335
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
LiveBench codingNot measured96.0%Only GPT-6.1 Sol measured
LMArena WebDev15821753GPT-6.1 Sol
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
Terminal-Bench 4 (Vals AI)Not measured55.0%Only GPT-6.1 Sol measured
Vibe Code Bench (Vals AI)Not measured88.9%Only GPT-6.1 Sol measured
Code migration (Vals AI)Not measured65.1%Only GPT-6.1 Sol measured
ProgramBench (Vals AI)Not measured3.0%Only GPT-6.1 Sol measured
IOI (Vals AI)Not measured96.9%Only GPT-6.1 Sol measured
SWE-bench Multimodal (Vals AI)Not measured43.5%Only GPT-6.1 Sol measured
CyberBench (Vals AI)Not measured39.3%Only GPT-6.1 Sol measured
SciCodeNot measured55.8%Only GPT-6.1 Sol measured
FrontierCodeNot measured50.2%Only GPT-6.1 Sol measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.22743.8GPT-6.1 Sol
LMArena Text: coding14571478GPT-6.1 Sol
LMArena Text: software and IT14531476GPT-6.1 Sol
LMArena WebDev: React15851754GPT-6.1 Sol
LMArena WebDev: HTML15581800GPT-6.1 Sol
LMArena WebDev: from an imageNot measured1702Only GPT-6.1 Sol measured
SciCodeNot measured9.2%Only GPT-6.1 Sol measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
AA Intelligence Index24.451.8GPT-6.1 Sol
Epoch Capabilities Index146.1168.4GPT-6.1 Sol
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: agents building web appsNot measured1306Only GPT-6.1 Sol measured
Design Arena: agents building mobile appsNot measured1213Only GPT-6.1 Sol measured
Design Arena: spreadsheetsNot measured1259Only GPT-6.1 Sol measured
LiveBench researchNot measured83.5%Only GPT-6.1 Sol measured
LiveBench browserNot measured88.0%Only GPT-6.1 Sol measured
LiveBench long agenticNot measured73.0%Only GPT-6.1 Sol measured
SREBench (Vals AI)Not measured50.8%Only GPT-6.1 Sol measured
Finance Agent (Vals AI)Not measured52.0%Only GPT-6.1 Sol measured
Tax Agent Bench (Vals AI)Not measured21.8%Only GPT-6.1 Sol measured
Legal Research Bench (Vals AI)Not measured38.5%Only GPT-6.1 Sol measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured6.3%Only GPT-6.1 Sol measured
Excel Modeling Benchmark (Vals AI)Not measured70.8%Only GPT-6.1 Sol measured
BioMysteryBench (Vals AI)Not measured79.6%Only GPT-6.1 Sol measured
Terminal-Bench-Science (Vals AI)Not measured52.9%Only GPT-6.1 Sol measured
Vals Science IndexNot measured59.6%Only GPT-6.1 Sol measured
Robo-bench (Vals AI)Not measured28.3%Only GPT-6.1 Sol measured
APEX-AgentsNot measured60.0%Only GPT-6.1 Sol measured
SpireClimbNot measured24.7%Only GPT-6.1 Sol measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
LiveBench reasoningNot measured92.6%Only GPT-6.1 Sol measured
MysteryMechanism (Vals AI)Not measured46.4%Only GPT-6.1 Sol measured
Humanity's Last Exam (Artificial Analysis run)Not measured52.9%Only GPT-6.1 Sol measured
GPQA Diamond (Epoch AI run)Not measured95.4%Only GPT-6.1 Sol measured
ARC-AGINot measured98.5%Only GPT-6.1 Sol measured
ARC-AGI-2Not measured94.2%Only GPT-6.1 Sol measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
Chess puzzlesNot measured68.0%Only GPT-6.1 Sol measured
Mystery game puzzlesNot measured80.0%Only GPT-6.1 Sol measured
EBR-benchNot measured54.3%Only GPT-6.1 Sol measured
LMArena Text: hard prompts14441463GPT-6.1 Sol
LMArena Text: expert14411489GPT-6.1 Sol
LMArena Text: hard prompts in English14491465GPT-6.1 Sol
LMArena Vision: diagramsNot measured1306Only GPT-6.1 Sol measured
LMArena Vision: homeworkNot measured1356Only GPT-6.1 Sol measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
OTIS Mock AIMENot measured100.0%Only GPT-6.1 Sol measured
FrontierMath, tiers 1 to 3Not measured93.7%Only GPT-6.1 Sol measured
FrontierMath, tier 4Not measured100.0%Only GPT-6.1 Sol measured
ProofBenchNot measured99.0%Only GPT-6.1 Sol measured
LMArena Text: math14261489GPT-6.1 Sol
LMArena Text: mathematical work14321513GPT-6.1 Sol
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index22
Knowledge benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
MedCode (Vals AI)Not measured48.8%Only GPT-6.1 Sol measured
SimpleQA VerifiedNot measured73.9%Only GPT-6.1 Sol measured
LMArena Text: science14461444DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481433DeepSeek V4 Flash 0423
LMArena Text: legal and government14391471GPT-6.1 Sol
LMArena Text: business and finance14251445GPT-6.1 Sol
FACTS Benchmark SuiteNot measured75.3%Only GPT-6.1 Sol measured
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
Design Arena: websites12071321GPT-6.1 Sol
Design Arena: UI components11621317GPT-6.1 Sol
Design Arena: game dev11961389GPT-6.1 Sol
Design Arena: data viz11271281GPT-6.1 Sol
Design Arena: 3D11881460GPT-6.1 Sol
Design Arena: all code categories12051345GPT-6.1 Sol
Design Arena: SVG1155Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveBench designNot measured82.1%Only GPT-6.1 Sol measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index114
General benchmarks for DeepSeek V4 Flash 0423 and GPT-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
Vals IndexNot measured63.9%Only GPT-6.1 Sol measured
LiveBench data analysisNot measured82.7%Only GPT-6.1 Sol measured
Public Benefits Bench (Vals AI)Not measured59.3%Only GPT-6.1 Sol measured
SAGE (Vals AI)Not measured46.5%Only GPT-6.1 Sol measured
MedScribe (Vals AI)Not measured86.5%Only GPT-6.1 Sol measured
Long context reasoning (AA-LCR)Not measured84.0%Only GPT-6.1 Sol measured
DTBench86.4%96.5%GPT-6.1 Sol
LMCA35.9%62.8%GPT-6.1 Sol
Furniture assemblyNot measured80.0%Only GPT-6.1 Sol measured
LMArena Text14321443GPT-6.1 Sol
LMArena Text: instruction following14211466GPT-6.1 Sol
LMArena Text: creative writing14031425GPT-6.1 Sol
LMArena VisionNot measured1288Only GPT-6.1 Sol measured
LMArena Text: English14411450GPT-6.1 Sol
LMArena Text: non-English14191433GPT-6.1 Sol
LMArena Text: Chinese14631487GPT-6.1 Sol
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: French14391460GPT-6.1 Sol
LMArena Text: Spanish14361439GPT-6.1 Sol
LMArena Text: Russian14271457GPT-6.1 Sol
LMArena Text: Polish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: multi-turn14491442DeepSeek V4 Flash 0423
LMArena Text: longer queries14341458GPT-6.1 Sol
LMArena Text: writing and language14101444GPT-6.1 Sol
LMArena Text: entertainment and media14001426GPT-6.1 Sol
LMArena Vision: EnglishNot measured1274Only GPT-6.1 Sol measured
LMArena Vision: reading textNot measured1289Only GPT-6.1 Sol measured
LMArena Vision: creative writingNot measured1301Only GPT-6.1 Sol 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-6.1 Sol
BenchmarkDeepSeek V4 Flash 0423GPT-6.1 SolLeader
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-6.1 Sol$0.0070Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
GPT-6.1 Sol$0.130Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
GPT-6.1 Sol$0.500Fits 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-6.1 Sol
SpecificationDeepSeek V4 Flash 0423OpenAI GPT-6.1 Sol
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026September 29, 2026
Context window1.05M1.05M
Input $/Mtok$0.14$2.00
Output $/Mtok$0.28$10.00
Coding indexNot benchmarked82.4
Independent measurements behind it15
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than GPT-6.1 Sol for coding?

Only GPT-6.1 Sol has a coding score, 82.4 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 35.7x cheaper ($0.28 vs $10.00 per million) and work measured by LMArena Text: science or LMArena Text: medicine and healthcare, where it leads.

Which is cheaper, DeepSeek V4 Flash 0423 or GPT-6.1 Sol?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or GPT-6.1 Sol?

GPT-6.1 Sol, with 1.05M tokens against 1.05M.

How many benchmarks is the DeepSeek V4 Flash 0423 vs GPT-6.1 Sol comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and GPT-6.1 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.

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