GPT-5.6 Luna vs Muse Spark Open
GPT-5.6 Luna leads Muse Spark Open on coding, 58.0 to 47.4 on the Vibe Coding Index, and GPT-5.6 Luna costs 3.5x less per output token ($1.20 vs $4.25 per million). Updated October 22, 2026; 26 benchmarks have a result for both.
GPT-5.6 Luna or Muse Spark Open: which to pick
Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 47.4 for Muse Spark Open.
Pick Muse Spark Open for work measured by LMArena WebDev or SciCode, where it leads.
- Shared results
- 26
- GPT-5.6 Luna only
- 93
- Muse Spark Open only
- 2
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
GPT-5.6 Luna
GPT-5.6 Luna scores 58.0 against 47.4.
6 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only GPT-5.6 Luna has a AA Intelligence Index result, 37.3.
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
Muse Spark Open
Muse Spark Open leads, 1317 against 1255.
Same board, both measured
General
Vals Index
No call
Only Muse Spark Open has a Vals Index result, 48.6%.
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, Muse Spark Open $0.0034 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 58.0 from 6 benchmarks, Muse Spark Open 47.4 from 4 benchmarks.
- Widest category
- Agentic work, 13.2 points apart on average over 8 shared benchmarks.
- Widest single gap
- LiveBench browser: GPT-5.6 Luna 68.0% against Muse Spark Open 36.0%, 32.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Luna $1.20 against Muse Spark Open $4.25 per million output tokens, 3.5x apart.
- Context window
- GPT-5.6 Luna takes 1.05M tokens, Muse Spark Open 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 | Muse Spark Open | Ties |
|---|---|---|---|---|
| Coding | 5 | 3 | 1 tie | |
| Intelligence | 1 | 0 | ||
| Agentic work | 4 | 4 | ||
| Reasoning | 2 | 1 | ||
| Web design | 1 | 2 | ||
| General | 2 | 0 | ||
| All shared boards | 15 | 10 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index53
| Benchmark | GPT-5.6 Luna | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | 73.6% | Tie |
| LMArena WebDev | 1518 | 1528 | Muse Spark Open |
| 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% | 6.6% | GPT-5.6 Luna |
| Vibe Code Bench (Vals AI) | 77.1% | 76.2% | GPT-5.6 Luna |
| Code migration (Vals AI) | 44.5% | 21.2% | GPT-5.6 Luna |
| 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% | 58.4% | Muse Spark Open |
| 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 | 1590.1 | GPT-5.6 Luna |
| LMArena Text: coding | 1466 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: software and IT | 1463 | Not measured | Only GPT-5.6 Luna measured |
| LMArena WebDev: React | 1508 | 1529 | Muse Spark Open |
| LMArena WebDev: HTML | 1520 | 1495 | GPT-5.6 Luna |
| 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 |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.6 Luna | Muse Spark Open | Leader |
|---|---|---|---|
| AA Intelligence Index | 37.3 | Not measured | Only GPT-5.6 Luna measured |
| Epoch Capabilities Index | 156.5 | 155.1 | GPT-5.6 Luna |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index44
| Benchmark | GPT-5.6 Luna | Muse Spark Open | Leader |
|---|---|---|---|
| AA Agentic Index | 42.1 | Not measured | Only GPT-5.6 Luna measured |
| LiveBench research | 51.0% | 80.3% | Muse Spark Open |
| LiveBench browser | 68.0% | 36.0% | GPT-5.6 Luna |
| LiveBench long agentic | 30.4% | 18.9% | GPT-5.6 Luna |
| SREBench (Vals AI) | 1.5% | Not measured | Only GPT-5.6 Luna measured |
| Finance Agent (Vals AI) | 55.0% | 61.3% | Muse Spark Open |
| Tax Agent Bench (Vals AI) | 24.8% | 26.3% | Muse Spark Open |
| Legal Research Bench (Vals AI) | 36.5% | 38.5% | Muse Spark Open |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 25.0% | Only Muse Spark Open measured |
| Excel Modeling Benchmark (Vals AI) | 67.1% | 53.7% | GPT-5.6 Luna |
| 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% | 33.4% | GPT-5.6 Luna |
| 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 25 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | GPT-5.6 Luna | Muse Spark Open | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | Not measured | Only GPT-5.6 Luna measured |
| LiveBench reasoning | 85.6% | 73.7% | GPT-5.6 Luna |
| 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% | 89.0% | GPT-5.6 Luna |
| Humanity's Last Exam (Artificial Analysis run) | 39.5% | 43.9% | Muse Spark Open |
| 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 | 1451 | 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 |
| 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
| Benchmark | GPT-5.6 Luna | Muse Spark Open | 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 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5.6 Luna | Muse Spark Open | 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 | 1399 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: legal and government | 1446 | 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 | 35.0% | Not measured | 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 index12
| Benchmark | GPT-5.6 Luna | Muse Spark Open | Leader |
|---|---|---|---|
| Design Arena: websites | 1255 | 1317 | Muse Spark Open |
| Design Arena: UI components | 1248 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: game dev | 1195 | 1284 | Muse Spark Open |
| Design Arena: data viz | 1212 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: 3D | 1121 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: all code categories | 1230 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: SVG | 1193 | Not measured | Only GPT-5.6 Luna measured |
| Design Arena: ASCII art | 1142 | Not measured | Only GPT-5.6 Luna measured |
| LiveBench design | 76.0% | 60.3% | GPT-5.6 Luna |
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.6 Luna | Muse Spark Open | Leader |
|---|---|---|---|
| Vals Index | Not measured | 48.6% | Only Muse Spark Open measured |
| LiveBench data analysis | 78.0% | 60.2% | GPT-5.6 Luna |
| Public Benefits Bench (Vals AI) | 61.2% | Not measured | Only GPT-5.6 Luna measured |
| SAGE (Vals AI) | 44.2% | 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% | 78.3% | GPT-5.6 Luna |
| 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 | 1437 | 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 | 1470 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: German | 1455 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Japanese | 1415 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Korean | 1415 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: French | 1458 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Spanish | 1446 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Russian | 1427 | Not measured | Only GPT-5.6 Luna measured |
| LMArena Text: Polish | 1405 | 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 | 1402 | 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 |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Luna | Muse Spark Open | 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 | Meta Muse Spark Open |
|---|---|---|
| Maker | OpenAI | Meta |
| Weights | No public weights listed | Open weights |
| Released | July 9, 2026 | October 15, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.20 | $1.25 |
| Output $/Mtok | $1.20 | $4.25 |
| Coding index | 58.0 | 47.4 |
| Independent measurements behind it | 6 | 4 |
| Cost per solved task | $0.04 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Luna better than Muse Spark Open for coding?
Pick GPT-5.6 Luna for coding: it scores 58.0 on the Vibe Coding Index against 47.4 for Muse Spark Open. Pick Muse Spark Open for work measured by LMArena WebDev or SciCode, where it leads.
Which is cheaper, GPT-5.6 Luna or Muse Spark Open?
GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; Muse Spark Open costs $1.25 and $4.25. Cost per solved task is known for GPT-5.6 Luna only.
Which has the bigger context window, GPT-5.6 Luna or Muse Spark Open?
GPT-5.6 Luna, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-5.6 Luna vs Muse Spark Open comparison based on?
26 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Luna's coding index rests on 6 independent benchmarks and Muse Spark Open's on 4. Where only one model has a result, the page says so instead of naming a winner.