DeepSeek V4 Flash 0731 vs GPT-5.6 Luna

GPT-5.6 Luna leads DeepSeek V4 Flash 0731 on coding, 58.0 to 51.8 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 3.0x less per output token ($0.396 vs $1.20 per million). Updated October 22, 2026; 54 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0731 Replace GPT-5.6 Luna

DeepSeek V4 Flash 0731DeepSeek

Coding: 51.8
Overall: 55.2
Output $/M: $0.396

GPT-5.6 LunaOpenAI

Coding: 58.0
Overall: 61.6
Output $/M: $1.20

vs boards won of 54 shared, 1 tied

DeepSeek V4 Flash 0731 or GPT-5.6 Luna: which to pick

Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731.

Pick DeepSeek V4 Flash 0731 for output tokens 3.0x cheaper ($0.396 vs $1.20 per million) and a lower cost per solved task ($0.01 against $0.04).

Model ADeepSeek V4 Flash 0731DeepSeek51.8/1004 independent benchmarks$0.01 per solved task Model BGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task

54165

Shared results: 54
DeepSeek V4 Flash 0731 only: 1
GPT-5.6 Luna only: 65
Like-for-like categories: 8 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
GPT-5.6 Luna
GPT-5.6 Luna scores 58.0 against 51.8.
4 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 34.3.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 42.1 against 41.0.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 89.9%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 86.2% against 86.0%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Luna
GPT-5.6 Luna leads, 1255 against 1237.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, GPT-5.6 Luna $0.0008 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-5.6 Luna $0.04.
Published attempt cost and pass rate

At a glance

Coding index: DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, GPT-5.6 Luna 58.0 from 6 benchmarks.
Widest category: Math, 17.3 points apart on average over 4 shared benchmarks.
Widest single gap: FrontierMath, tier 4: DeepSeek V4 Flash 0731 24.4% against GPT-5.6 Luna 61.0%, 36.6 points apart on a 0 to 100 scale.
Output price: DeepSeek V4 Flash 0731 $0.396 against GPT-5.6 Luna $1.20 per million output tokens, 3.0x apart.
Context window: DeepSeek V4 Flash 0731 takes 1.05M tokens, GPT-5.6 Luna 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
Category	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Ties
Coding	2	11	1 tie
Intelligence	0	2
Agentic work	3	4
Reasoning	4	5
Math	0	4
Knowledge	1	5
Web design	2	6
General	1	3
All shared boards	13	40	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index211

Coding benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
LiveBench coding	Not measured	73.6%	Only GPT-5.6 Luna measured
LMArena WebDev	Not measured	1518	Only GPT-5.6 Luna measured
AA Coding Index	69.1	71.4	GPT-5.6 Luna
LiveCodeBench (Vals AI)	87.3%	Not measured	Only DeepSeek V4 Flash 0731 measured
SWE-bench Verified (Vals AI)	88.8%	93.0%	GPT-5.6 Luna
Terminal-Bench 4 (Vals AI)	18.7%	11.6%	DeepSeek V4 Flash 0731
Vibe Code Bench (Vals AI)	74.7%	77.1%	GPT-5.6 Luna
Code migration (Vals AI)	38.6%	44.5%	GPT-5.6 Luna
ProgramBench (Vals AI)	0.0%	0.0%	Tie
IOI (Vals AI)	32.7%	61.8%	GPT-5.6 Luna
Terminal-Bench 2.1 (Vals AI)	67.0%	79.0%	GPT-5.6 Luna
Vibe Code Bench 1-100 (Vals AI)	Not measured	22.6%	Only GPT-5.6 Luna measured
SkillsBench (Vals AI)	50.7%	60.5%	GPT-5.6 Luna
CyberBench (Vals AI)	72.1%	73.6%	GPT-5.6 Luna
SciCode	50.3%	53.6%	GPT-5.6 Luna
FrontierCode	18.8%	39.8%	GPT-5.6 Luna
WeirdML	63.0%	60.9%	DeepSeek V4 Flash 0731
ALE-Bench	1306.1	1667.4	GPT-5.6 Luna
LMArena Text: coding	Not measured	1466	Only GPT-5.6 Luna measured
LMArena Text: software and IT	Not measured	1463	Only GPT-5.6 Luna measured
LMArena WebDev: React	Not measured	1508	Only GPT-5.6 Luna measured
LMArena WebDev: HTML	Not measured	1520	Only GPT-5.6 Luna measured
LMArena WebDev: from an image	Not measured	1517	Only GPT-5.6 Luna measured
SciCode	Not measured	6.2%	Only GPT-5.6 Luna measured
Neither model has a result on the other 15 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02

Intelligence benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
AA Intelligence Index	34.3	37.3	GPT-5.6 Luna
Epoch Capabilities Index	154.8	156.5	GPT-5.6 Luna

Agentic workLike-for-likePublic boards, shown as published, kept out of the index34

Agentic work benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
AA Agentic Index	41.0	42.1	GPT-5.6 Luna
LiveBench research	Not measured	51.0%	Only GPT-5.6 Luna measured
LiveBench browser	Not measured	68.0%	Only GPT-5.6 Luna measured
LiveBench long agentic	Not measured	30.4%	Only GPT-5.6 Luna measured
SREBench (Vals AI)	Not measured	1.5%	Only GPT-5.6 Luna measured
Finance Agent (Vals AI)	49.5%	55.0%	GPT-5.6 Luna
Tax Agent Bench (Vals AI)	28.1%	24.8%	DeepSeek V4 Flash 0731
Legal Research Bench (Vals AI)	30.3%	36.5%	GPT-5.6 Luna
Excel Modeling Benchmark (Vals AI)	57.0%	67.1%	GPT-5.6 Luna
BioMysteryBench (Vals AI)	64.4%	61.5%	DeepSeek V4 Flash 0731
Terminal-Bench-Science (Vals AI)	4.3%	0.0%	DeepSeek V4 Flash 0731
Vals Science Index	Not measured	25.3%	Only GPT-5.6 Luna measured
APEX-Agents	Not measured	43.0%	Only GPT-5.6 Luna measured
BALROG	Not measured	45.6%	Only GPT-5.6 Luna measured
Vending-Bench 2	Not measured	$4,095	Only GPT-5.6 Luna measured
Neither model has a result on the other 26 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index45

Reasoning benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
GPQA Diamond	89.9%	91.7%	GPT-5.6 Luna
LiveBench reasoning	Not measured	85.6%	Only GPT-5.6 Luna measured
MysteryMechanism (Vals AI)	Not measured	14.4%	Only GPT-5.6 Luna measured
MMMU Pro (Vals AI)	Not measured	85.0%	Only GPT-5.6 Luna measured
GPQA Diamond (Artificial Analysis run)	90.8%	91.1%	GPT-5.6 Luna
Humanity's Last Exam (Artificial Analysis run)	38.6%	39.5%	GPT-5.6 Luna
GPQA Diamond (Epoch AI run)	91.0%	91.6%	GPT-5.6 Luna
ARC-AGI	89.0%	88.0%	DeepSeek V4 Flash 0731
ARC-AGI-2	61.4%	59.5%	DeepSeek V4 Flash 0731
SimpleBench	61.1%	46.8%	DeepSeek V4 Flash 0731
Chess puzzles	32.0%	43.0%	GPT-5.6 Luna
Mystery game puzzles	34.0%	21.0%	DeepSeek V4 Flash 0731
LMArena Text: hard prompts	Not measured	1451	Only GPT-5.6 Luna measured
LMArena Text: expert	Not measured	1478	Only GPT-5.6 Luna measured
LMArena Text: hard prompts in English	Not measured	1460	Only GPT-5.6 Luna measured
LMArena Vision: diagrams	Not measured	1273	Only GPT-5.6 Luna measured
LMArena Vision: homework	Not measured	1282	Only GPT-5.6 Luna measured
Kagi LLM Benchmark	Not measured	49.1%	Only GPT-5.6 Luna measured
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index04

Math benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
OTIS Mock AIME	94.4%	98.3%	GPT-5.6 Luna
FrontierMath, tiers 1 to 3	57.5%	82.1%	GPT-5.6 Luna
FrontierMath, tier 4	24.4%	61.0%	GPT-5.6 Luna
ProofBench	56.0%	60.0%	GPT-5.6 Luna
LMArena Text: math	Not measured	1459	Only GPT-5.6 Luna measured
LMArena Text: mathematical work	Not measured	1470	Only GPT-5.6 Luna measured
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15

Knowledge benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
MMLU Pro	86.2%	86.0%	DeepSeek V4 Flash 0731
LegalBench (Vals AI)	77.7%	84.0%	GPT-5.6 Luna
CorpFin (Vals AI)	61.9%	64.2%	GPT-5.6 Luna
TaxEval (Vals AI)	70.7%	76.2%	GPT-5.6 Luna
MortgageTax (Vals AI)	Not measured	67.3%	Only GPT-5.6 Luna measured
MedCode (Vals AI)	41.4%	42.4%	GPT-5.6 Luna
SimpleQA Verified	33.6%	41.0%	GPT-5.6 Luna
LMArena Text: science	Not measured	1433	Only GPT-5.6 Luna measured
LMArena Text: medicine and healthcare	Not measured	1399	Only GPT-5.6 Luna measured
LMArena Text: legal and government	Not measured	1446	Only GPT-5.6 Luna measured
LMArena Text: business and finance	Not measured	1439	Only GPT-5.6 Luna measured
FACTS Benchmark Suite	Not measured	35.0%	Only GPT-5.6 Luna measured
Neither model has a result on the other 6 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index26

Web design benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
Design Arena: websites	1237	1255	GPT-5.6 Luna
Design Arena: UI components	1233	1248	GPT-5.6 Luna
Design Arena: game dev	1207	1194	DeepSeek V4 Flash 0731
Design Arena: data viz	1180	1211	GPT-5.6 Luna
Design Arena: 3D	1208	1121	DeepSeek V4 Flash 0731
Design Arena: all code categories	1229	1231	GPT-5.6 Luna
Design Arena: SVG	1184	1194	GPT-5.6 Luna
Design Arena: ASCII art	1090	1142	GPT-5.6 Luna
LiveBench design	Not measured	76.0%	Only GPT-5.6 Luna measured

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

General benchmarks for DeepSeek V4 Flash 0731 and GPT-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	Leader
LiveBench data analysis	Not measured	78.0%	Only GPT-5.6 Luna measured
Public Benefits Bench (Vals AI)	Not measured	61.2%	Only GPT-5.6 Luna measured
SAGE (Vals AI)	Not measured	44.2%	Only GPT-5.6 Luna measured
MedScribe (Vals AI)	80.4%	84.4%	GPT-5.6 Luna
Vals Multimodal Index	Not measured	69.1%	Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)	79.7%	83.7%	GPT-5.6 Luna
DTBench	90.9%	89.1%	DeepSeek V4 Flash 0731
LMCA	41.7%	48.5%	GPT-5.6 Luna
Surface Evolver Bench	Not measured	61.9%	Only GPT-5.6 Luna measured
Furniture assembly	Not measured	42.5%	Only GPT-5.6 Luna measured
LMArena Text	Not measured	1431	Only GPT-5.6 Luna measured
LMArena Text: instruction following	Not measured	1437	Only GPT-5.6 Luna measured
LMArena Text: creative writing	Not measured	1396	Only GPT-5.6 Luna measured
LMArena Vision	Not measured	1257	Only GPT-5.6 Luna measured
LMArena Text: English	Not measured	1441	Only GPT-5.6 Luna measured
LMArena Text: non-English	Not measured	1417	Only GPT-5.6 Luna measured
LMArena Text: Chinese	Not measured	1470	Only GPT-5.6 Luna measured
LMArena Text: German	Not measured	1455	Only GPT-5.6 Luna measured
LMArena Text: Japanese	Not measured	1415	Only GPT-5.6 Luna measured
LMArena Text: Korean	Not measured	1415	Only GPT-5.6 Luna measured
LMArena Text: French	Not measured	1458	Only GPT-5.6 Luna measured
LMArena Text: Spanish	Not measured	1446	Only GPT-5.6 Luna measured
LMArena Text: Russian	Not measured	1427	Only GPT-5.6 Luna measured
LMArena Text: Polish	Not measured	1405	Only GPT-5.6 Luna measured
LMArena Text: multi-turn	Not measured	1434	Only GPT-5.6 Luna measured
LMArena Text: longer queries	Not measured	1436	Only GPT-5.6 Luna measured
LMArena Text: writing and language	Not measured	1419	Only GPT-5.6 Luna measured
LMArena Text: entertainment and media	Not measured	1402	Only GPT-5.6 Luna measured
LMArena Vision: English	Not measured	1263	Only GPT-5.6 Luna measured
LMArena Vision: Chinese	Not measured	1294	Only GPT-5.6 Luna measured
LMArena Vision: reading text	Not measured	1264	Only GPT-5.6 Luna measured
LMArena Vision: humor	Not measured	1190	Only GPT-5.6 Luna measured
LMArena Vision: creative writing	Not measured	1257	Only GPT-5.6 Luna measured
LMArena Document	Not measured	1457	Only GPT-5.6 Luna 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-5.6 Luna
Benchmark	DeepSeek V4 Flash 0731	GPT-5.6 Luna	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-5.6 Luna$0.0008Fits 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-5.6 Luna$0.014Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.032Fits in one request

GPT-5.6 Luna$0.052Fits 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-5.6 Luna
Specification	DeepSeek V4 Flash 0731	OpenAI GPT-5.6 Luna
Maker	DeepSeek	OpenAI
Weights	Open weights	No public weights listed
Released	July 31, 2026	July 9, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.14	$0.20
Output $/Mtok	$0.396	$1.20
Coding index	51.8	58.0
Independent measurements behind it	4	6
Cost per solved task	$0.01	$0.04
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than GPT-5.6 Luna for coding?

Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731. Pick DeepSeek V4 Flash 0731 for output tokens 3.0x cheaper ($0.396 vs $1.20 per million) and a lower cost per solved task ($0.01 against $0.04).

Which is cheaper, DeepSeek V4 Flash 0731 or GPT-5.6 Luna?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.396 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and GPT-5.6 Luna $0.04.

Which has the bigger context window, DeepSeek V4 Flash 0731 or GPT-5.6 Luna?

GPT-5.6 Luna, with 1.05M tokens against 1.05M.

How many benchmarks is the DeepSeek V4 Flash 0731 vs GPT-5.6 Luna comparison based on?

54 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and GPT-5.6 Luna's on 6. 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-5.6 Luna: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

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