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DeepSeek V4 Flash 0731 vs GPT-4

Updated October 21, 2026. 6 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

DeepSeek V4 Flash 0731DeepSeek
Coding
51.8
Overall
34.3
Output $/M
$0.396
6
GPT-4OpenAI
Coding
No data
Overall
6.7
Output $/M
$60.00
0
vs boards won of 6 shared

Decision reading

Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; GPT-4 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
6
DeepSeek V4 Flash 0731 only
49
GPT-4 only
39
Like-for-like categories
4 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 0731 51.8 from 4 benchmarks, GPT-4 not benchmarked.
Widest category
Coding, 56.0 points apart on average over 1 shared benchmark.
Widest single gap
AA Coding Index: DeepSeek V4 Flash 0731 69.1 against GPT-4 13.1, 56.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0731 $0.396 against GPT-4 $60.00 per million output tokens, 151.5x apart.
Context window
DeepSeek V4 Flash 0731 takes 1.05M tokens, GPT-4 8K.

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 0731BarsGPT-4Ties
Coding10
Intelligence20
Reasoning10
General20
All shared boards60
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
SWE-bench VerifiedNot measured22.4%Only GPT-4 measured
SWE-bench LiteNot measured39.7%Only GPT-4 measured
SWE-bench (full test set)Not measured12.5%Only GPT-4 measured
AA Coding Index69.113.1DeepSeek V4 Flash 0731
LiveCodeBench (Vals AI)87.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
SWE-bench Verified (Vals AI)88.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench 4 (Vals AI)18.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Vibe Code Bench (Vals AI)74.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Code migration (Vals AI)38.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
IOI (Vals AI)32.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench 2.1 (Vals AI)67.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
SkillsBench (Vals AI)50.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
CyberBench (Vals AI)72.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
SciCode50.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierCode18.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
WeirdML63.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ALE-Bench1306.1Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: codingNot measured1209Only GPT-4 measured
LMArena Text: software and ITNot measured1195Only GPT-4 measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
AA Intelligence Index34.36.7DeepSeek V4 Flash 0731
Epoch Capabilities Index154.8125.7DeepSeek V4 Flash 0731
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
AA Agentic Index41.0Not measuredOnly DeepSeek V4 Flash 0731 measured
Finance Agent (Vals AI)49.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
Tax Agent Bench (Vals AI)28.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
Legal Research Bench (Vals AI)30.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
Excel Modeling Benchmark (Vals AI)57.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
BioMysteryBench (Vals AI)64.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
GPQA Diamond89.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
GPQA Diamond (Artificial Analysis run)90.8%34.9%DeepSeek V4 Flash 0731
Humanity's Last Exam (Artificial Analysis run)38.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
GPQA Diamond (Epoch AI run)91.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI89.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI-261.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
SimpleBench61.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
Chess puzzles32.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
Mystery game puzzles34.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
BIG-Bench HardNot measured75.1%Only GPT-4 measured
LMArena Text: hard promptsNot measured1200Only GPT-4 measured
LMArena Text: expertNot measured1149Only GPT-4 measured
LMArena Text: hard prompts in EnglishNot measured1209Only GPT-4 measured
Neither model has a result on the other 8 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
OTIS Mock AIME94.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tiers 1 to 357.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tier 424.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProofBench56.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
GSM8KNot measured92.0%Only GPT-4 measured
LMArena Text: mathNot measured1230Only GPT-4 measured
LMArena Text: mathematical workNot measured1228Only GPT-4 measured
Neither model has a result on the other 6 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
MMLU Pro86.2%Not measuredOnly DeepSeek V4 Flash 0731 measured
LegalBench (Vals AI)77.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
CorpFin (Vals AI)61.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
TaxEval (Vals AI)70.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
MedCode (Vals AI)41.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
MMLU Pro (Artificial Analysis run)Not measured56.2%Only GPT-4 measured
SimpleQA Verified33.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
MMLUNot measured86.4%Only GPT-4 measured
AI2 Reasoning ChallengeNot measured96.3%Only GPT-4 measured
LMArena Text: scienceNot measured1177Only GPT-4 measured
LMArena Text: medicine and healthcareNot measured1145Only GPT-4 measured
LMArena Text: legal and governmentNot measured1191Only GPT-4 measured
LMArena Text: business and financeNot measured1145Only GPT-4 measured
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
Design Arena: websites1238Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: UI components1235Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: game dev1208Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: data viz1180Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: 3D1209Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: all code categories1230Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: SVG1185Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: ASCII art1090Not measuredOnly DeepSeek V4 Flash 0731 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
MedScribe (Vals AI)80.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
IFBenchNot measured33.2%Only GPT-4 measured
Long context reasoning (AA-LCR)79.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
DTBench90.9%62.7%DeepSeek V4 Flash 0731
LMCA41.7%17.1%DeepSeek V4 Flash 0731
HellaSwagNot measured95.3%Only GPT-4 measured
WinoGrandeNot measured87.5%Only GPT-4 measured
LMArena TextNot measured1206Only GPT-4 measured
LMArena Text: instruction followingNot measured1201Only GPT-4 measured
LMArena Text: creative writingNot measured1191Only GPT-4 measured
LMArena Text: EnglishNot measured1220Only GPT-4 measured
LMArena Text: non-EnglishNot measured1194Only GPT-4 measured
LMArena Text: ChineseNot measured1184Only GPT-4 measured
LMArena Text: GermanNot measured1198Only GPT-4 measured
LMArena Text: JapaneseNot measured1137Only GPT-4 measured
LMArena Text: KoreanNot measured1087Only GPT-4 measured
LMArena Text: FrenchNot measured1220Only GPT-4 measured
LMArena Text: SpanishNot measured1197Only GPT-4 measured
LMArena Text: RussianNot measured1195Only GPT-4 measured
LMArena Text: PolishNot measured1265Only GPT-4 measured
LMArena Text: multi-turnNot measured1206Only GPT-4 measured
LMArena Text: longer queriesNot measured1190Only GPT-4 measured
LMArena Text: writing and languageNot measured1219Only GPT-4 measured
LMArena Text: entertainment and mediaNot measured1184Only GPT-4 measured
Neither model has a result on the other 22 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0731 and GPT-4
BenchmarkDeepSeek V4 Flash 0731GPT-4Leader
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 0731$0.0003Fits in one request
GPT-4$0.060Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0082Fits in one request
GPT-4$1.68Exceeds the context window

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.032Fits in one request
GPT-4$6.60Exceeds the context window

DeepSeek V4 Flash 0731 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 0731 and GPT-4
SpecificationDeepSeek V4 Flash 0731OpenAI GPT-4
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJuly 31, 2026May 28, 2023
Context window1.05M8K
Input $/Mtok$0.14$30.00
Output $/Mtok$0.396$60.00
Coding index51.8Not benchmarked
Independent measurements behind it40
Cost per solved task$0.01Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than GPT-4 for coding?

Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; GPT-4 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, DeepSeek V4 Flash 0731 or GPT-4?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.396 per million output tokens; GPT-4 costs $30.00 and $60.00. Cost per solved task is known for DeepSeek V4 Flash 0731 only.

Which has the bigger context window, DeepSeek V4 Flash 0731 or GPT-4?

DeepSeek V4 Flash 0731, with 1.05M tokens against 8K.

How many benchmarks is the DeepSeek V4 Flash 0731 vs GPT-4 comparison based on?

6 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and GPT-4's on 0. Where only one model has a result, the page says so instead of naming a winner.

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