DeepSeek V4 Flash 0731 vs GPT-5.1

DeepSeek V4 Flash 0731 leads GPT-5.1 on coding, 51.8 to 40.4 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 35.7x less per output token ($0.28 vs $10.00 per million). Updated October 21, 2026; 35 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0731 Replace GPT-5.1

DeepSeek V4 Flash 0731DeepSeek

Coding: 51.8
Overall: 55.2
Output $/M: $0.28

GPT-5.1OpenAI

Coding: 40.4
Overall: 55.0
Output $/M: $10.00

vs boards won of 35 shared

DeepSeek V4 Flash 0731 or GPT-5.1: which to pick

Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 40.4 for GPT-5.1.

Pick GPT-5.1 for work measured by Chess puzzles or MMLU Pro, where it leads.

Model ADeepSeek V4 Flash 0731DeepSeek51.8/1004 independent benchmarks$0.01 per solved task Model BGPT-5.1OpenAI40.4/1003 independent benchmarks$1.02 per solved task

352066

Shared results: 35
DeepSeek V4 Flash 0731 only: 20
GPT-5.1 only: 66
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.

Coding
Vibe Coding Index, six public coding benchmarks
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 scores 51.8 against 40.4.
4 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 34.3 against 24.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only DeepSeek V4 Flash 0731 has a AA Agentic Index result, 41.0.
Directional only
Reasoning
GPQA Diamond
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 89.9% against 86.6%.
Same board, both measured
Math
AIME
No call
Only GPT-5.1 has a AIME result, 93.3%.
Directional only
Knowledge
MMLU Pro
GPT-5.1
GPT-5.1 leads, 86.4% against 86.2%.
Same board, both measured
Web design
Design Arena: websites
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 1238 against 1187.
Same board, both measured
Long documents
Listed context window
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, GPT-5.1 $0.0063 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.01, GPT-5.1 $1.02.
Published attempt cost and pass rate

At a glance

Coding index: DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, GPT-5.1 40.4 from 3 benchmarks.
Widest category: Coding, 18.4 points apart on average over 5 shared benchmarks.
Widest single gap: Vibe Code Bench (Vals AI): DeepSeek V4 Flash 0731 74.7% against GPT-5.1 24.6%, 50.1 points apart on a 0 to 100 scale.
Output price: DeepSeek V4 Flash 0731 $0.28 against GPT-5.1 $10.00 per million output tokens, 35.7x apart.
Context window: DeepSeek V4 Flash 0731 takes 1.05M tokens, GPT-5.1 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
Category	DeepSeek V4 Flash 0731	GPT-5.1
Coding	5	0
Intelligence	2	0
Reasoning	8	1
Math	1	0
Knowledge	0	6
Web design	6	2
General	1	3
All shared boards	23	12

CodingLike-for-likeSix of these boards feed the Vibe Coding Index50

Coding benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
SWE-bench Verified	Not measured	66.0%	Only GPT-5.1 measured
LMArena WebDev	Not measured	1396	Only GPT-5.1 measured
AA Coding Index	69.1	49.4	DeepSeek V4 Flash 0731
LiveCodeBench (Vals AI)	87.3%	86.5%	DeepSeek V4 Flash 0731
SWE-bench Verified (Vals AI)	88.8%	69.8%	DeepSeek V4 Flash 0731
Terminal-Bench 4 (Vals AI)	18.7%	Not measured	Only DeepSeek V4 Flash 0731 measured
Vibe Code Bench (Vals AI)	74.7%	24.6%	DeepSeek V4 Flash 0731
Code migration (Vals AI)	38.6%	Not measured	Only DeepSeek V4 Flash 0731 measured
ProgramBench (Vals AI)	0.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
IOI (Vals AI)	32.7%	Not measured	Only DeepSeek V4 Flash 0731 measured
Terminal-Bench 2.1 (Vals AI)	67.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
SkillsBench (Vals AI)	50.7%	Not measured	Only DeepSeek V4 Flash 0731 measured
CyberBench (Vals AI)	72.1%	Not measured	Only DeepSeek V4 Flash 0731 measured
LiveCodeBench (Artificial Analysis run)	Not measured	86.8%	Only GPT-5.1 measured
SciCode	50.3%	Not measured	Only DeepSeek V4 Flash 0731 measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	45.5%	Only GPT-5.1 measured
Terminal-Bench	Not measured	47.6%	Only GPT-5.1 measured
FrontierCode	18.8%	Not measured	Only DeepSeek V4 Flash 0731 measured
GSO-Bench	Not measured	13.7%	Only GPT-5.1 measured
WeirdML	63.0%	60.8%	DeepSeek V4 Flash 0731
ALE-Bench	1306.1	Not measured	Only DeepSeek V4 Flash 0731 measured
LMArena Text: coding	Not measured	1453	Only GPT-5.1 measured
LMArena Text: software and IT	Not measured	1454	Only GPT-5.1 measured
LMArena WebDev: React	Not measured	1307	Only GPT-5.1 measured
LMArena WebDev: HTML	Not measured	1405	Only GPT-5.1 measured
LMArena WebDev: from an image	Not measured	1421	Only GPT-5.1 measured
Neither model has a result on the other 13 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
AA Intelligence Index	34.3	24.7	DeepSeek V4 Flash 0731
Epoch Capabilities Index	154.8	149.8	DeepSeek V4 Flash 0731

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared

Agentic work benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
AA Agentic Index	41.0	Not measured	Only DeepSeek V4 Flash 0731 measured
Finance Agent (Vals AI)	49.5%	Not measured	Only DeepSeek V4 Flash 0731 measured
Tax Agent Bench (Vals AI)	28.1%	Not measured	Only DeepSeek V4 Flash 0731 measured
Legal Research Bench (Vals AI)	30.3%	Not measured	Only DeepSeek V4 Flash 0731 measured
Excel Modeling Benchmark (Vals AI)	57.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
BioMysteryBench (Vals AI)	64.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)	4.3%	Not measured	Only DeepSeek V4 Flash 0731 measured
τ²-Bench Telecom	Not measured	81.9%	Only GPT-5.1 measured
DeepResearch Bench	Not measured	42.8%	Only GPT-5.1 measured
Vending-Bench 2	Not measured	$1,473	Only GPT-5.1 measured
Neither model has a result on the other 31 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index81

Reasoning benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
GPQA Diamond	89.9%	86.6%	DeepSeek V4 Flash 0731
MMMU Pro (Vals AI)	Not measured	83.2%	Only GPT-5.1 measured
GPQA Diamond (Artificial Analysis run)	90.8%	87.3%	DeepSeek V4 Flash 0731
Humanity's Last Exam (Artificial Analysis run)	38.6%	28.5%	DeepSeek V4 Flash 0731
GPQA Diamond (Epoch AI run)	91.0%	87.6%	DeepSeek V4 Flash 0731
ARC-AGI	89.0%	72.8%	DeepSeek V4 Flash 0731
ARC-AGI-2	61.4%	17.6%	DeepSeek V4 Flash 0731
SimpleBench	61.1%	53.2%	DeepSeek V4 Flash 0731
Chess puzzles	32.0%	42.0%	GPT-5.1
Mystery game puzzles	34.0%	19.0%	DeepSeek V4 Flash 0731
VPCT	Not measured	58.7%	Only GPT-5.1 measured
LMArena Text: hard prompts	Not measured	1457	Only GPT-5.1 measured
LMArena Text: expert	Not measured	1470	Only GPT-5.1 measured
LMArena Text: hard prompts in English	Not measured	1462	Only GPT-5.1 measured
LMArena Vision: diagrams	Not measured	1264	Only GPT-5.1 measured
LMArena Vision: homework	Not measured	1272	Only GPT-5.1 measured
Neither model has a result on the other 6 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index10

Math benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
AIME	Not measured	93.3%	Only GPT-5.1 measured
MGSM (Vals AI)	Not measured	93.0%	Only GPT-5.1 measured
AA Math Index	Not measured	94.0	Only GPT-5.1 measured
AIME 2025 (Artificial Analysis run)	Not measured	94.0%	Only GPT-5.1 measured
OTIS Mock AIME	94.4%	88.6%	DeepSeek V4 Flash 0731
FrontierMath, tiers 1 to 3	57.5%	Not measured	Only DeepSeek V4 Flash 0731 measured
FrontierMath, tier 4	24.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
ProofBench	56.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
LMArena Text: math	Not measured	1446	Only GPT-5.1 measured
LMArena Text: mathematical work	Not measured	1449	Only GPT-5.1 measured
Neither model has a result on the other 3 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06

Knowledge benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
MMLU Pro	86.2%	86.4%	GPT-5.1
LegalBench (Vals AI)	77.7%	85.7%	GPT-5.1
CaseLaw (Vals AI)	Not measured	73.4%	Only GPT-5.1 measured
CorpFin (Vals AI)	61.9%	63.8%	GPT-5.1
TaxEval (Vals AI)	70.7%	74.9%	GPT-5.1
MortgageTax (Vals AI)	Not measured	61.4%	Only GPT-5.1 measured
MedQA (Vals AI)	Not measured	96.4%	Only GPT-5.1 measured
MedCode (Vals AI)	41.4%	52.7%	GPT-5.1
MMLU Pro (Artificial Analysis run)	Not measured	87.0%	Only GPT-5.1 measured
SimpleQA Verified	33.6%	48.0%	GPT-5.1
LMArena Text: science	Not measured	1459	Only GPT-5.1 measured
LMArena Text: medicine and healthcare	Not measured	1456	Only GPT-5.1 measured
LMArena Text: legal and government	Not measured	1459	Only GPT-5.1 measured
LMArena Text: business and finance	Not measured	1431	Only GPT-5.1 measured
FACTS Benchmark Suite	Not measured	45.0%	Only GPT-5.1 measured
Neither model has a result on the other 3 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index62

Web design benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
Design Arena: websites	1238	1187	DeepSeek V4 Flash 0731
Design Arena: UI components	1235	1166	DeepSeek V4 Flash 0731
Design Arena: game dev	1208	1179	DeepSeek V4 Flash 0731
Design Arena: data viz	1180	1204	GPT-5.1
Design Arena: 3D	1209	1061	DeepSeek V4 Flash 0731
Design Arena: all code categories	1230	1171	DeepSeek V4 Flash 0731
Design Arena: SVG	1185	1149	DeepSeek V4 Flash 0731
Design Arena: ASCII art	1090	1119	GPT-5.1
Neither model has a result on the other 1 board here

GeneralLike-for-likePublic boards, shown as published, kept out of the index13

General benchmarks for DeepSeek V4 Flash 0731 and GPT-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
SAGE (Vals AI)	Not measured	43.2%	Only GPT-5.1 measured
MedScribe (Vals AI)	80.4%	88.1%	GPT-5.1
IFBench	Not measured	72.9%	Only GPT-5.1 measured
Long context reasoning (AA-LCR)	79.7%	80.0%	GPT-5.1
DTBench	90.9%	90.1%	DeepSeek V4 Flash 0731
LMCA	41.7%	43.9%	GPT-5.1
CL-bench	Not measured	23.7%	Only GPT-5.1 measured
CL-bench Life	Not measured	17.3%	Only GPT-5.1 measured
LMArena Text	Not measured	1443	Only GPT-5.1 measured
LMArena Text: instruction following	Not measured	1443	Only GPT-5.1 measured
LMArena Text: creative writing	Not measured	1427	Only GPT-5.1 measured
LMArena Vision	Not measured	1250	Only GPT-5.1 measured
LMArena Text: English	Not measured	1451	Only GPT-5.1 measured
LMArena Text: non-English	Not measured	1431	Only GPT-5.1 measured
LMArena Text: Chinese	Not measured	1495	Only GPT-5.1 measured
LMArena Text: German	Not measured	1438	Only GPT-5.1 measured
LMArena Text: Japanese	Not measured	1453	Only GPT-5.1 measured
LMArena Text: Korean	Not measured	1401	Only GPT-5.1 measured
LMArena Text: French	Not measured	1450	Only GPT-5.1 measured
LMArena Text: Spanish	Not measured	1433	Only GPT-5.1 measured
LMArena Text: Russian	Not measured	1435	Only GPT-5.1 measured
LMArena Text: Polish	Not measured	1440	Only GPT-5.1 measured
LMArena Text: multi-turn	Not measured	1450	Only GPT-5.1 measured
LMArena Text: longer queries	Not measured	1448	Only GPT-5.1 measured
LMArena Text: writing and language	Not measured	1428	Only GPT-5.1 measured
LMArena Text: entertainment and media	Not measured	1415	Only GPT-5.1 measured
LMArena Vision: English	Not measured	1252	Only GPT-5.1 measured
LMArena Vision: Chinese	Not measured	1270	Only GPT-5.1 measured
LMArena Vision: reading text	Not measured	1255	Only GPT-5.1 measured
LMArena Vision: humor	Not measured	1263	Only GPT-5.1 measured
LMArena Vision: captioning	Not measured	1252	Only GPT-5.1 measured
LMArena Vision: recognizing things	Not measured	1232	Only GPT-5.1 measured
LMArena Vision: creative writing	Not measured	1266	Only GPT-5.1 measured
LMArena Document	Not measured	1403	Only GPT-5.1 measured
Neither model has a result on the other 12 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-5.1
Benchmark	DeepSeek V4 Flash 0731	GPT-5.1	Leader
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-5.1$0.0063Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0078Fits in one request

GPT-5.1$0.092Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.031Fits in one request

GPT-5.1$0.350Fits in one request

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-5.1
Specification	DeepSeek V4 Flash 0731	OpenAI GPT-5.1
Maker	DeepSeek	OpenAI
Weights	Open weights	No public weights listed
Released	July 31, 2026	November 13, 2025
Context window	1.05M	400K
Input $/Mtok	$0.14	$1.25
Output $/Mtok	$0.28	$10.00
Coding index	51.8	40.4
Independent measurements behind it	4	3
Cost per solved task	$0.01	$1.02
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than GPT-5.1 for coding?

Pick DeepSeek V4 Flash 0731 for coding: it scores 51.8 on the Vibe Coding Index against 40.4 for GPT-5.1. Pick GPT-5.1 for work measured by Chess puzzles or MMLU Pro, where it leads.

Which is cheaper, DeepSeek V4 Flash 0731 or GPT-5.1?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; GPT-5.1 costs $1.25 and $10.00. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and GPT-5.1 $1.02.

Which has the bigger context window, DeepSeek V4 Flash 0731 or GPT-5.1?

DeepSeek V4 Flash 0731, with 1.05M tokens against 400K.

How many benchmarks is the DeepSeek V4 Flash 0731 vs GPT-5.1 comparison based on?

35 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-5.1's on 3. Where only one model has a result, the page says so instead of naming a winner.

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DeepSeek V4 Flash 0731 or GPT-5.1: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next