Enter opens the highlighted result. Esc closes.

DeepSeek V4 Flash Vision Exp vs GPT-5.6 Luna

GPT-5.6 Luna leads DeepSeek V4 Flash Vision Exp on the Artificial Analysis Intelligence Index, 37.3 to 34.8, at about the same output price ($1.20 vs $1.32 per million). Updated October 22, 2026; 14 benchmarks have a result for both.

DeepSeek V4 Flash Vision ExpDeepSeek
Coding
No data
Overall
56.4
Output $/M
$1.32
5
GPT-5.6 LunaOpenAI
Coding
58.0
Overall
61.6
Output $/M
$1.20
9
vs boards won of 14 shared

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

Only GPT-5.6 Luna has a coding score, 58.0 on the Vibe Coding Index; DeepSeek V4 Flash Vision Exp has none, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash Vision Exp for work measured by AA Agentic Index or LiveBench research, where it leads.

Shared results
14
DeepSeek V4 Flash Vision Exp only
0
GPT-5.6 Luna only
105
Like-for-like categories
6 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 Vision Exp not benchmarked, GPT-5.6 Luna 58.0 from 6 benchmarks.
Widest category
Coding, 15.4 points apart on average over 3 shared benchmarks.
Widest single gap
LiveBench coding: DeepSeek V4 Flash Vision Exp 37.6% against GPT-5.6 Luna 73.6%, 36.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash Vision Exp $1.32 against GPT-5.6 Luna $1.20 per million output tokens, 1.1x apart.
Context window
DeepSeek V4 Flash Vision Exp 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
CategoryDeepSeek V4 Flash Vision ExpBarsGPT-5.6 LunaTies
Coding03
Intelligence01
Agentic work31
Reasoning12
Web design01
General11
All shared boards59
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
LiveBench coding37.6%73.6%GPT-5.6 Luna
LMArena WebDevNot measured1518Only GPT-5.6 Luna measured
AA Coding Index65.071.4GPT-5.6 Luna
SWE-bench Verified (Vals AI)Not measured93.0%Only GPT-5.6 Luna measured
Terminal-Bench 4 (Vals AI)Not measured11.6%Only GPT-5.6 Luna measured
Vibe Code Bench (Vals AI)Not measured77.1%Only GPT-5.6 Luna measured
Code migration (Vals AI)Not measured44.5%Only GPT-5.6 Luna measured
ProgramBench (Vals AI)Not measured0.0%Only GPT-5.6 Luna measured
IOI (Vals AI)Not measured61.8%Only GPT-5.6 Luna measured
Terminal-Bench 2.1 (Vals AI)Not measured79.0%Only GPT-5.6 Luna measured
Vibe Code Bench 1-100 (Vals AI)Not measured22.6%Only GPT-5.6 Luna measured
SkillsBench (Vals AI)Not measured60.5%Only GPT-5.6 Luna measured
CyberBench (Vals AI)Not measured73.6%Only GPT-5.6 Luna measured
SciCode49.7%53.6%GPT-5.6 Luna
FrontierCodeNot measured39.8%Only GPT-5.6 Luna measured
WeirdMLNot measured60.9%Only GPT-5.6 Luna measured
ALE-BenchNot measured1667.4Only GPT-5.6 Luna measured
LMArena Text: codingNot measured1466Only GPT-5.6 Luna measured
LMArena Text: software and ITNot measured1463Only GPT-5.6 Luna measured
LMArena WebDev: ReactNot measured1508Only GPT-5.6 Luna measured
LMArena WebDev: HTMLNot measured1520Only GPT-5.6 Luna measured
LMArena WebDev: from an imageNot measured1517Only GPT-5.6 Luna measured
SciCodeNot measured6.2%Only GPT-5.6 Luna measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
AA Intelligence Index34.837.3GPT-5.6 Luna
Epoch Capabilities IndexNot measured156.5Only GPT-5.6 Luna measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index31
Agentic work benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
AA Agentic Index47.542.1DeepSeek V4 Flash Vision Exp
LiveBench research69.2%51.0%DeepSeek V4 Flash Vision Exp
LiveBench browser64.0%68.0%GPT-5.6 Luna
LiveBench long agentic39.0%30.4%DeepSeek V4 Flash Vision Exp
SREBench (Vals AI)Not measured1.5%Only GPT-5.6 Luna measured
Finance Agent (Vals AI)Not measured55.0%Only GPT-5.6 Luna measured
Tax Agent Bench (Vals AI)Not measured24.8%Only GPT-5.6 Luna measured
Legal Research Bench (Vals AI)Not measured36.5%Only GPT-5.6 Luna measured
Excel Modeling Benchmark (Vals AI)Not measured67.1%Only GPT-5.6 Luna measured
BioMysteryBench (Vals AI)Not measured61.5%Only GPT-5.6 Luna measured
Terminal-Bench-Science (Vals AI)Not measured0.0%Only GPT-5.6 Luna measured
Vals Science IndexNot measured25.3%Only GPT-5.6 Luna measured
APEX-AgentsNot measured43.0%Only GPT-5.6 Luna measured
BALROGNot measured45.6%Only GPT-5.6 Luna measured
Vending-Bench 2Not measured$4,095Only 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 index12
Reasoning benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
GPQA DiamondNot measured91.7%Only GPT-5.6 Luna measured
LiveBench reasoning85.4%85.6%GPT-5.6 Luna
MysteryMechanism (Vals AI)Not measured14.4%Only GPT-5.6 Luna measured
MMMU Pro (Vals AI)Not measured85.0%Only GPT-5.6 Luna measured
GPQA Diamond (Artificial Analysis run)91.3%91.1%DeepSeek V4 Flash Vision Exp
Humanity's Last Exam (Artificial Analysis run)34.5%39.5%GPT-5.6 Luna
GPQA Diamond (Epoch AI run)Not measured91.6%Only GPT-5.6 Luna measured
ARC-AGINot measured88.0%Only GPT-5.6 Luna measured
ARC-AGI-2Not measured59.5%Only GPT-5.6 Luna measured
SimpleBenchNot measured46.8%Only GPT-5.6 Luna measured
Chess puzzlesNot measured43.0%Only GPT-5.6 Luna measured
Mystery game puzzlesNot measured21.0%Only GPT-5.6 Luna measured
LMArena Text: hard promptsNot measured1451Only GPT-5.6 Luna measured
LMArena Text: expertNot measured1478Only GPT-5.6 Luna measured
LMArena Text: hard prompts in EnglishNot measured1460Only GPT-5.6 Luna measured
LMArena Vision: diagramsNot measured1273Only GPT-5.6 Luna measured
LMArena Vision: homeworkNot measured1282Only GPT-5.6 Luna measured
Kagi LLM BenchmarkNot measured49.1%Only GPT-5.6 Luna measured
Neither model has a result on the other 4 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
OTIS Mock AIMENot measured98.3%Only GPT-5.6 Luna measured
FrontierMath, tiers 1 to 3Not measured82.1%Only GPT-5.6 Luna measured
FrontierMath, tier 4Not measured61.0%Only GPT-5.6 Luna measured
ProofBenchNot measured60.0%Only GPT-5.6 Luna measured
LMArena Text: mathNot measured1459Only GPT-5.6 Luna measured
LMArena Text: mathematical workNot measured1470Only GPT-5.6 Luna measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Knowledge benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
MMLU ProNot measured86.0%Only GPT-5.6 Luna measured
LegalBench (Vals AI)Not measured84.0%Only GPT-5.6 Luna measured
CorpFin (Vals AI)Not measured64.2%Only GPT-5.6 Luna measured
TaxEval (Vals AI)Not measured76.2%Only GPT-5.6 Luna measured
MortgageTax (Vals AI)Not measured67.3%Only GPT-5.6 Luna measured
MedCode (Vals AI)Not measured42.4%Only GPT-5.6 Luna measured
SimpleQA VerifiedNot measured41.0%Only GPT-5.6 Luna measured
LMArena Text: scienceNot measured1433Only GPT-5.6 Luna measured
LMArena Text: medicine and healthcareNot measured1399Only GPT-5.6 Luna measured
LMArena Text: legal and governmentNot measured1446Only GPT-5.6 Luna measured
LMArena Text: business and financeNot measured1439Only GPT-5.6 Luna measured
FACTS Benchmark SuiteNot measured35.0%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 index01
Web design benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
Design Arena: websitesNot measured1255Only GPT-5.6 Luna measured
Design Arena: UI componentsNot measured1248Only GPT-5.6 Luna measured
Design Arena: game devNot measured1195Only GPT-5.6 Luna measured
Design Arena: data vizNot measured1212Only GPT-5.6 Luna measured
Design Arena: 3DNot measured1121Only GPT-5.6 Luna measured
Design Arena: all code categoriesNot measured1230Only GPT-5.6 Luna measured
Design Arena: SVGNot measured1193Only GPT-5.6 Luna measured
Design Arena: ASCII artNot measured1142Only GPT-5.6 Luna measured
LiveBench design70.7%76.0%GPT-5.6 Luna
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
General benchmarks for DeepSeek V4 Flash Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
LiveBench data analysis79.5%78.0%DeepSeek V4 Flash Vision Exp
Public Benefits Bench (Vals AI)Not measured61.2%Only GPT-5.6 Luna measured
SAGE (Vals AI)Not measured44.2%Only GPT-5.6 Luna measured
MedScribe (Vals AI)Not measured84.4%Only GPT-5.6 Luna measured
Vals Multimodal IndexNot measured69.1%Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)81.3%83.7%GPT-5.6 Luna
DTBenchNot measured89.1%Only GPT-5.6 Luna measured
LMCANot measured48.5%Only GPT-5.6 Luna measured
Surface Evolver BenchNot measured61.9%Only GPT-5.6 Luna measured
Furniture assemblyNot measured42.5%Only GPT-5.6 Luna measured
LMArena TextNot measured1431Only GPT-5.6 Luna measured
LMArena Text: instruction followingNot measured1437Only GPT-5.6 Luna measured
LMArena Text: creative writingNot measured1396Only GPT-5.6 Luna measured
LMArena VisionNot measured1257Only GPT-5.6 Luna measured
LMArena Text: EnglishNot measured1441Only GPT-5.6 Luna measured
LMArena Text: non-EnglishNot measured1417Only GPT-5.6 Luna measured
LMArena Text: ChineseNot measured1470Only GPT-5.6 Luna measured
LMArena Text: GermanNot measured1455Only GPT-5.6 Luna measured
LMArena Text: JapaneseNot measured1415Only GPT-5.6 Luna measured
LMArena Text: KoreanNot measured1415Only GPT-5.6 Luna measured
LMArena Text: FrenchNot measured1458Only GPT-5.6 Luna measured
LMArena Text: SpanishNot measured1446Only GPT-5.6 Luna measured
LMArena Text: RussianNot measured1427Only GPT-5.6 Luna measured
LMArena Text: PolishNot measured1405Only GPT-5.6 Luna measured
LMArena Text: multi-turnNot measured1434Only GPT-5.6 Luna measured
LMArena Text: longer queriesNot measured1436Only GPT-5.6 Luna measured
LMArena Text: writing and languageNot measured1419Only GPT-5.6 Luna measured
LMArena Text: entertainment and mediaNot measured1402Only GPT-5.6 Luna measured
LMArena Vision: EnglishNot measured1263Only GPT-5.6 Luna measured
LMArena Vision: ChineseNot measured1294Only GPT-5.6 Luna measured
LMArena Vision: reading textNot measured1264Only GPT-5.6 Luna measured
LMArena Vision: humorNot measured1190Only GPT-5.6 Luna measured
LMArena Vision: creative writingNot measured1257Only GPT-5.6 Luna measured
LMArena DocumentNot measured1457Only 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 Vision Exp and GPT-5.6 Luna
BenchmarkDeepSeek V4 Flash Vision ExpGPT-5.6 LunaLeader
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 Vision Exp$0.0011Fits in one request
GPT-5.6 Luna$0.0008Fits in one request

GPT-5.6 Luna costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash Vision Exp$0.026Fits in one request
GPT-5.6 Luna$0.014Fits in one request

GPT-5.6 Luna costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash Vision Exp$0.101Fits in one request
GPT-5.6 Luna$0.052Fits in one request

GPT-5.6 Luna 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 Vision Exp and GPT-5.6 Luna
SpecificationDeepSeek V4 Flash Vision ExpOpenAI GPT-5.6 Luna
MakerDeepSeekOpenAI
WeightsOpen weightsNo public weights listed
ReleasedAugust 21, 2026July 9, 2026
Context window1.05M1.05M
Input $/Mtok$0.44$0.20
Output $/Mtok$1.32$1.20
Coding indexNot benchmarked58.0
Independent measurements behind it16
Cost per solved taskNot computable$0.04
SourceOpenRouter listingOpenRouter listing

Questions

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

Only GPT-5.6 Luna has a coding score, 58.0 on the Vibe Coding Index; DeepSeek V4 Flash Vision Exp has none, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash Vision Exp for work measured by AA Agentic Index or LiveBench research, where it leads.

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

DeepSeek V4 Flash Vision Exp costs $0.44 per million input tokens and $1.32 per million output tokens; GPT-5.6 Luna costs $0.20 and $1.20. Cost per solved task is known for GPT-5.6 Luna only.

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

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

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

14 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash Vision Exp's coding index rests on 1 independent benchmark and GPT-5.6 Luna's on 6. Where only one model has a result, the page says so instead of naming a winner.

Compare next