DeepSeek V3 0324 vs GPT-5.6 Luna
GPT-5.6 Luna leads DeepSeek V3 0324 on the Artificial Analysis Intelligence Index, 37.3 to 9.7, at about the same output price ($1.20 vs $1.07 per million). Updated October 22, 2026; 18 benchmarks have a result for both.
vs boards won of 18 shared
DeepSeek V3 0324 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 V3 0324 has none, so the two cannot be ranked on coding.
Pick DeepSeek V3 0324 for output tokens 1.1x cheaper ($1.07 vs $1.20 per million).
Model ADeepSeek V3 0324DeepSeekNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task
- Shared results
- 18
- DeepSeek V3 0324 only
- 18
- GPT-5.6 Luna only
- 102
- 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
No call
Only GPT-5.6 Luna has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 37.3 against 9.7.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Luna
GPT-5.6 Luna leads, 42.1 against 0.8.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Luna
GPT-5.6 Luna leads, 91.7% against 61.6%.
Same board, both measured
Math
AIME
No call
Only DeepSeek V3 0324 has a AIME result, 52.2%.
Directional only
Knowledge
MMLU Pro
GPT-5.6 Luna
GPT-5.6 Luna leads, 86.0% against 79.5%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5.6 Luna has a Design Arena: websites result, 1255.
Directional only
Long documents
Listed context window
GPT-5.6 Luna
GPT-5.6 Luna takes 1.05M tokens against 164K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Luna
DeepSeek V3 0324 $0.0008, GPT-5.6 Luna $0.0008 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Luna has the number, $0.04.
Directional only
At a glance
- Coding index
- DeepSeek V3 0324 not benchmarked, GPT-5.6 Luna 58.0 from 6 benchmarks.
- Widest category
- Math, 60.6 points apart on average over 1 shared benchmark.
- Widest single gap
- OTIS Mock AIME: DeepSeek V3 0324 37.8% against GPT-5.6 Luna 98.3%, 60.6 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V3 0324 $1.07 against GPT-5.6 Luna $1.20 per million output tokens, 1.1x apart.
- Context window
- DeepSeek V3 0324 takes 164K 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.
| Category | DeepSeek V3 0324 | Bars | GPT-5.6 Luna | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 5 | ||
| Math | 0 | 1 | ||
| Knowledge | 0 | 4 | ||
| General | 0 | 3 | ||
| All shared boards | 0 | 18 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| SWE-bench Verified | 42.0% | Not measured | Only DeepSeek V3 0324 measured |
| 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 | 21.2 | 71.4 | GPT-5.6 Luna |
| LiveCodeBench (Vals AI) | 65.5% | Not measured | Only DeepSeek V3 0324 measured |
| SWE-bench Verified (Vals AI) | Not measured | 93.0% | Only GPT-5.6 Luna measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 11.6% | Only GPT-5.6 Luna measured |
| Vibe Code Bench (Vals AI) | Not measured | 77.1% | Only GPT-5.6 Luna measured |
| Code migration (Vals AI) | Not measured | 44.5% | Only GPT-5.6 Luna measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only GPT-5.6 Luna measured |
| IOI (Vals AI) | Not measured | 61.8% | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 79.0% | Only GPT-5.6 Luna measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 22.6% | Only GPT-5.6 Luna measured |
| SkillsBench (Vals AI) | Not measured | 60.5% | Only GPT-5.6 Luna measured |
| CyberBench (Vals AI) | Not measured | 73.6% | Only GPT-5.6 Luna measured |
| LiveCodeBench (Artificial Analysis run) | 40.5% | Not measured | Only DeepSeek V3 0324 measured |
| SciCode | 39.0% | 53.6% | GPT-5.6 Luna |
| Terminal-Bench Hard (Artificial Analysis run) | 15.2% | Not measured | Only DeepSeek V3 0324 measured |
| FrontierCode | Not measured | 39.8% | Only GPT-5.6 Luna measured |
| WeirdML | 36.1% | 60.9% | GPT-5.6 Luna |
| ALE-Bench | Not measured | 1667.4 | Only GPT-5.6 Luna measured |
| 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 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| AA Intelligence Index | 9.7 | 37.3 | GPT-5.6 Luna |
| Epoch Capabilities Index | Not measured | 156.5 | Only GPT-5.6 Luna measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| AA Agentic Index | 0.8 | 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) | Not measured | 55.0% | Only GPT-5.6 Luna measured |
| Tax Agent Bench (Vals AI) | Not measured | 24.8% | Only GPT-5.6 Luna measured |
| Legal Research Bench (Vals AI) | Not measured | 36.5% | Only GPT-5.6 Luna measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 67.1% | Only GPT-5.6 Luna measured |
| BioMysteryBench (Vals AI) | Not measured | 61.5% | Only GPT-5.6 Luna measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 0.0% | Only GPT-5.6 Luna measured |
| Vals Science Index | Not measured | 25.3% | Only GPT-5.6 Luna measured |
| τ²-Bench Telecom | 47.1% | Not measured | Only DeepSeek V3 0324 measured |
| APEX-Agents | Not measured | 43.0% | Only GPT-5.6 Luna measured |
| METR time horizons | 49.6% | Not measured | Only DeepSeek V3 0324 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 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| GPQA Diamond | 61.6% | 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) | 65.5% | 91.1% | GPT-5.6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 4.7% | 39.5% | GPT-5.6 Luna |
| GPQA Diamond (Epoch AI run) | 67.6% | 91.6% | GPT-5.6 Luna |
| ARC-AGI | Not measured | 88.0% | Only GPT-5.6 Luna measured |
| ARC-AGI-2 | Not measured | 59.5% | Only GPT-5.6 Luna measured |
| SimpleBench | 27.2% | 46.8% | GPT-5.6 Luna |
| Chess puzzles | Not measured | 43.0% | Only GPT-5.6 Luna measured |
| Mystery game puzzles | Not measured | 21.0% | Only GPT-5.6 Luna measured |
| 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 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| AIME | 52.2% | Not measured | Only DeepSeek V3 0324 measured |
| MATH 500 (Vals AI) | 88.6% | Not measured | Only DeepSeek V3 0324 measured |
| MGSM (Vals AI) | 91.7% | Not measured | Only DeepSeek V3 0324 measured |
| AA Math Index | 41.0 | Not measured | Only DeepSeek V3 0324 measured |
| AIME 2025 (Artificial Analysis run) | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| OTIS Mock AIME | 37.8% | 98.3% | GPT-5.6 Luna |
| FrontierMath, tiers 1 to 3 | Not measured | 82.1% | Only GPT-5.6 Luna measured |
| FrontierMath, tier 4 | Not measured | 61.0% | Only GPT-5.6 Luna measured |
| ProofBench | Not measured | 60.0% | Only GPT-5.6 Luna measured |
| MATH level 5 | 75.5% | Not measured | Only DeepSeek V3 0324 measured |
| 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 |
| MathArena | 7.1% | Not measured | Only DeepSeek V3 0324 measured |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| MMLU Pro | 79.5% | 86.0% | GPT-5.6 Luna |
| LegalBench (Vals AI) | 77.7% | 84.0% | GPT-5.6 Luna |
| CorpFin (Vals AI) | 54.7% | 64.2% | GPT-5.6 Luna |
| TaxEval (Vals AI) | 71.1% | 76.2% | GPT-5.6 Luna |
| MortgageTax (Vals AI) | Not measured | 67.3% | Only GPT-5.6 Luna measured |
| MedQA (Vals AI) | 82.0% | Not measured | Only DeepSeek V3 0324 measured |
| MedCode (Vals AI) | Not measured | 42.4% | Only GPT-5.6 Luna measured |
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only DeepSeek V3 0324 measured |
| SimpleQA Verified | Not measured | 41.0% | Only GPT-5.6 Luna measured |
| 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 designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V3 0324 | GPT-5.6 Luna | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1255 | Only GPT-5.6 Luna measured |
| Design Arena: UI components | Not measured | 1248 | Only GPT-5.6 Luna measured |
| Design Arena: game dev | Not measured | 1195 | Only GPT-5.6 Luna measured |
| Design Arena: data viz | Not measured | 1212 | Only GPT-5.6 Luna measured |
| Design Arena: 3D | Not measured | 1121 | Only GPT-5.6 Luna measured |
| Design Arena: all code categories | Not measured | 1230 | Only GPT-5.6 Luna measured |
| Design Arena: SVG | Not measured | 1193 | Only GPT-5.6 Luna measured |
| Design Arena: ASCII art | Not measured | 1142 | Only GPT-5.6 Luna measured |
| LiveBench design | Not measured | 76.0% | Only GPT-5.6 Luna measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | DeepSeek V3 0324 | 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) | Not measured | 84.4% | Only GPT-5.6 Luna measured |
| Vals Multimodal Index | Not measured | 69.1% | Only GPT-5.6 Luna measured |
| IFBench | 41.0% | Not measured | Only DeepSeek V3 0324 measured |
| Long context reasoning (AA-LCR) | 40.7% | 83.7% | GPT-5.6 Luna |
| DTBench | 64.8% | 89.1% | GPT-5.6 Luna |
| LMCA | 15.5% | 48.5% | GPT-5.6 Luna |
| Fiction.LiveBench | 50.0% | Not measured | Only DeepSeek V3 0324 measured |
| Creative writing (Lech Mazur) | 77.0% | Not measured | Only DeepSeek V3 0324 measured |
| 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 |
| EQ-Bench 4 | Not measured | 1156 | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V3 0324 | 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 V3 0324$0.0008Fits 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 V3 0324$0.017Fits 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 V3 0324$0.065Exceeds the context window
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.
| Specification | DeepSeek V3 0324 | OpenAI GPT-5.6 Luna |
|---|---|---|
| Maker | DeepSeek | OpenAI |
| Weights | Open weights | No public weights listed |
| Released | March 24, 2025 | July 9, 2026 |
| Context window | 164K | 1.05M |
| Input $/Mtok | $0.27 | $0.20 |
| Output $/Mtok | $1.07 | $1.20 |
| Coding index | Not benchmarked | 58.0 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $0.04 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V3 0324 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 V3 0324 has none, so the two cannot be ranked on coding. Pick DeepSeek V3 0324 for output tokens 1.1x cheaper ($1.07 vs $1.20 per million).
Which is cheaper, DeepSeek V3 0324 or GPT-5.6 Luna?
DeepSeek V3 0324 costs $0.27 per million input tokens and $1.07 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 V3 0324 or GPT-5.6 Luna?
GPT-5.6 Luna, with 1.05M tokens against 164K.
How many benchmarks is the DeepSeek V3 0324 vs GPT-5.6 Luna comparison based on?
18 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3 0324's coding index rests on 0 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.