GPT-5.6 Luna vs Hy4
Hy4 leads GPT-5.6 Luna on coding, 65.2 to 55.3 on the Vibe Coding Index, at about the same output price ($1.2505 vs $1.20 per million). Updated November 5, 2026; 4 benchmarks have a result for both.
GPT-5.6 Luna or Hy4: which to pick
Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 55.3 for GPT-5.6 Luna, though on 2 benchmarks against 5.
Pick GPT-5.6 Luna for output tokens 1.0x cheaper ($1.20 vs $1.2505 per million) and a larger context window (1.05M against 1.05M tokens).
- Shared results
- 4
- GPT-5.6 Luna only
- 114
- Hy4 only
- 2
- Like-for-like categories
- 2 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
Hy4
Hy4 scores 65.2 against 55.3.
5 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5.6 Luna has a AA Intelligence Index result, 23.8.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Luna has a AA Agentic Index result, 42.1.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Luna has a GPQA Diamond result, 91.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Luna has a MMLU Pro result, 86.0%.
Directional only
Web design
Design Arena: websites
No call
Only GPT-5.6 Luna has a Design Arena: websites result, 1253.
Directional only
General
Vals Index
No call
Only Hy4 has a Vals Index result, 59.4%.
Directional only
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
GPT-5.6 Luna
GPT-5.6 Luna $0.0008, Hy4 $0.0010 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
- GPT-5.6 Luna 55.3 from 5 benchmarks, Hy4 65.2 from 2 benchmarks.
- Widest category
- Coding, 20.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- Terminal-Bench 4 (Vals AI): GPT-5.6 Luna 11.6% against Hy4 39.4%, 37.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Luna $1.20 against Hy4 $1.2505 per million output tokens, 1.0x apart.
- Context window
- GPT-5.6 Luna takes 1.05M tokens, Hy4 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 | GPT-5.6 Luna | Bars | Hy4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Agentic work | 0 | 2 | ||
| All shared boards | 0 | 4 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| LMArena WebDev | 1519 | Not measured | Only GPT-5.6 Luna measured |
| AA Coding Index | 71.4 | Not measured | Only GPT-5.6 Luna measured |
| SWE-bench Verified (Vals AI) | 93.0% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 4 (Vals AI) | 11.6% | 39.4% | Hy4 |
| Vibe Code Bench (Vals AI) | 77.1% | 81.0% | Hy4 |
| Code migration (Vals AI) | 44.5% | Not measured | Only GPT-5.6 Luna measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| IOI (Vals AI) | 61.8% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 (Vals AI) | 79.0% | Not measured | Only GPT-5.6 Luna measured |
| Vibe Code Bench 1-100 (Vals AI) | 22.6% | Not measured | Only GPT-5.6 Luna measured |
| SkillsBench (Vals AI) | 60.5% | Not measured | Only GPT-5.6 Luna measured |
| CyberBench (Vals AI) | 73.6% | Not measured | Only GPT-5.6 Luna measured |
| SciCode | 53.6% | Not measured | Only GPT-5.6 Luna measured |
| FrontierCode | 39.8% | Not measured | Only GPT-5.6 Luna measured |
| WeirdML | 60.9% | Not measured | Only GPT-5.6 Luna measured |
| ALE-Bench | 1667.4 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: coding | 1466 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: software and IT | 1464 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: React | 1508 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: HTML | 1521 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: from an image | 1517 | Not measured | Only GPT-5.6 Luna measured |
| SciCode | 6.2% | Not measured | Only GPT-5.6 Luna measured |
| GameBench 2 | 54.0 | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 2.1 | 75.7% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 3.0 | 14.3% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench 4.0 | 17.3% | Not measured | Only GPT-5.6 Luna measured |
| CursorBench 4.0 | 35.9% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 23.8 | Not measured | Only GPT-5.6 Luna measured |
| Epoch Capabilities Index | 156.8 | Not measured | Only GPT-5.6 Luna measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| AA Agentic Index | 42.1 | Not measured | Only GPT-5.6 Luna measured |
| SREBench (Vals AI) | 1.5% | Not measured | Only GPT-5.6 Luna measured |
| Finance Agent (Vals AI) | 55.0% | Not measured | Only GPT-5.6 Luna measured |
| Tax Agent Bench (Vals AI) | 24.8% | 34.4% | Hy4 |
| Legal Research Bench (Vals AI) | 36.5% | 41.4% | Hy4 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.5% | Only Hy4 measured |
| Excel Modeling Benchmark (Vals AI) | 67.1% | Not measured | Only GPT-5.6 Luna measured |
| BioMysteryBench (Vals AI) | 61.5% | Not measured | Only GPT-5.6 Luna measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only GPT-5.6 Luna measured |
| Vals Science Index | 25.3% | Not measured | Only GPT-5.6 Luna measured |
| APEX-Agents | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| BALROG | 45.6% | Not measured | Only GPT-5.6 Luna measured |
| Vending-Bench 2 | $4,095 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | Not measured | Only GPT-5.6 Luna measured |
| MysteryMechanism (Vals AI) | 14.4% | Not measured | Only GPT-5.6 Luna measured |
| MMMU Pro (Vals AI) | 85.0% | Not measured | Only GPT-5.6 Luna measured |
| GPQA Diamond (Artificial Analysis run) | 91.1% | Not measured | Only GPT-5.6 Luna measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.5% | Not measured | Only GPT-5.6 Luna measured |
| GPQA Diamond (Epoch AI run) | 91.6% | Not measured | Only GPT-5.6 Luna measured |
| ARC-AGI | 88.0% | Not measured | Only GPT-5.6 Luna measured |
| ARC-AGI-2 | 59.5% | Not measured | Only GPT-5.6 Luna measured |
| SimpleBench | 46.8% | Not measured | Only GPT-5.6 Luna measured |
| Chess puzzles | 43.0% | Not measured | Only GPT-5.6 Luna measured |
| Mystery game puzzles | 21.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: hard prompts | 1452 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: expert | 1478 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: hard prompts in English | 1460 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: diagrams | 1273 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: homework | 1282 | Not measured | Only GPT-5.6 Luna measured |
| Kagi LLM Benchmark | 49.1% | Not measured | Only GPT-5.6 Luna measured |
| GoBench | 1091 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only GPT-5.6 Luna measured |
| FrontierMath, tiers 1 to 3 | 82.1% | Not measured | Only GPT-5.6 Luna measured |
| FrontierMath, tier 4 | 61.0% | Not measured | Only GPT-5.6 Luna measured |
| ProofBench | 60.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: math | 1459 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: mathematical work | 1470 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| MMLU Pro | 86.0% | Not measured | Only GPT-5.6 Luna measured |
| LegalBench (Vals AI) | 84.0% | Not measured | Only GPT-5.6 Luna measured |
| CorpFin (Vals AI) | 64.2% | Not measured | Only GPT-5.6 Luna measured |
| TaxEval (Vals AI) | 76.2% | Not measured | Only GPT-5.6 Luna measured |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Luna measured |
| MedCode (Vals AI) | 42.4% | Not measured | Only GPT-5.6 Luna measured |
| SimpleQA Verified | 41.0% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: science | 1433 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: medicine and healthcare | 1398 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: legal and government | 1445 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: business and finance | 1439 | Not measured | Only GPT-5.6 Luna measured |
| FACTS Benchmark Suite | 55.3% | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1253 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: UI components | 1245 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: game dev | 1194 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: data viz | 1209 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: 3D | 1118 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: all code categories | 1229 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: SVG | 1188 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: ASCII art | 1142 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index34 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 59.4% | Only Hy4 measured |
| Public Benefits Bench (Vals AI) | 61.2% | Not measured | Only GPT-5.6 Luna measured |
| MedScribe (Vals AI) | 84.4% | Not measured | Only GPT-5.6 Luna measured |
| Vals Multimodal Index | 69.1% | Not measured | Only GPT-5.6 Luna measured |
| Long context reasoning (AA-LCR) | 83.7% | Not measured | Only GPT-5.6 Luna measured |
| DTBench | 89.1% | Not measured | Only GPT-5.6 Luna measured |
| LMCA | 48.5% | Not measured | Only GPT-5.6 Luna measured |
| Surface Evolver Bench | 61.9% | Not measured | Only GPT-5.6 Luna measured |
| Furniture assembly | 42.5% | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text | 1431 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: instruction following | 1438 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: creative writing | 1396 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: English | 1441 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: non-English | 1417 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Chinese | 1471 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: German | 1455 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Japanese | 1416 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Korean | 1414 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: French | 1457 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Spanish | 1445 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Russian | 1428 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Polish | 1404 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: multi-turn | 1434 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: longer queries | 1436 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: writing and language | 1419 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: entertainment and media | 1401 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: English | 1263 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: Chinese | 1294 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: reading text | 1264 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: humor | 1190 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Vision: creative writing | 1257 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Document | 1457 | Not measured | Only GPT-5.6 Luna measured |
| EQ-Bench 4 | 1146 | Not measured | Only GPT-5.6 Luna measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Luna | Hy4 | 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
GPT-5.6 Luna costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Luna costs less
Agent loop
200K input + 10K output tokens
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 | OpenAI GPT-5.6 Luna | Tencent Hy4 |
|---|---|---|
| Maker | OpenAI | Tencent |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | November 4, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.20 | $0.417 |
| Output $/Mtok | $1.20 | $1.2505 |
| Coding index | 55.3 | 65.2 |
| Independent measurements behind it | 5 | 2 |
| Cost per solved task | $0.04 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Luna better than Hy4 for coding?
Pick Hy4 for coding: it scores 65.2 on the Vibe Coding Index against 55.3 for GPT-5.6 Luna, though on 2 benchmarks against 5. Pick GPT-5.6 Luna for output tokens 1.0x cheaper ($1.20 vs $1.2505 per million) and a larger context window (1.05M against 1.05M tokens).
Which is cheaper, GPT-5.6 Luna or Hy4?
GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; Hy4 costs $0.417 and $1.2505. Cost per solved task is known for GPT-5.6 Luna only.
Which has the bigger context window, GPT-5.6 Luna or Hy4?
GPT-5.6 Luna, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-5.6 Luna vs Hy4 comparison based on?
4 benchmarks have a result for both models as of November 5, 2026. GPT-5.6 Luna's coding index rests on 5 independent benchmarks and Hy4's on 2. Where only one model has a result, the page says so instead of naming a winner.