Model comparison
GPT-5.6 Luna vs Muse Spark 1.3
GPT-5.6 Luna and Muse Spark 1.3 score almost the same on the Noometry Index (54.6 vs 54.8), so choose on price, context window or the category you care about most.
Last verified . 36 shared benchmarks.
MetaSummary
- They share 36 benchmarks with published results for both. GPT-5.6 Luna scores higher in 2 categories and Muse Spark 1.3 in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.6 Luna leads 58.5 to 42.6.
- The biggest single-benchmark swing is NYT Connections (extended): 69.4% for GPT-5.6 Luna and 85.1% for Muse Spark 1.3.
- GPT-5.6 Luna is cheaper at $0.20 / $1.20 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.3.
- GPT-5.6 Luna accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-5.6 Luna | Muse Spark 1.3 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 54.6 | 54.8 |
| Released | 2026-07-09 | 2026-09-02 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $0.20 | $1.25 |
| Output $ / M tokens | $1.20 | $4.25 |
| Results tracked | 52 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
GPT-5.6 Luna: 54.5 (#28), Muse Spark 1.3: 56.6 (#21)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| CursorBench | 35.9% | 41.6% |
| LMArena WebDev | 1519 | 1657 |
| SciCode | 53.6% | 59.7% |
| LMArena Coding | 1466 | 1514 |
| DeepSWE | 67.2% | — |
| FrontierCode | 39.8% | — |
| WeirdML | 60.9% | — |
| ALE-Bench | 1,667 | — |
Agentic & Tool Use Muse Spark 1.3 leads
GPT-5.6 Luna: 34.4 (#45), Muse Spark 1.3: 38.6 (#30)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | 43% | 57.8% |
| GDP.pdf | 22.7% | 27.6% |
| BALROG | 45.6% | — |
| Vending-Bench 2 | 4,095 | — |
Reasoning Muse Spark 1.3 leads
GPT-5.6 Luna: 47.6 (#43), Muse Spark 1.3: 54.0 (#27)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| NYT Connections (extended) | 69.4% | 85.1% |
| CritPt | 20.6% | 26% |
| Chess Puzzles | 40% | 38% |
| LMArena Hard Prompts | 1451 | 1503 |
| Mystery Game Puzzles | 21% | 25% |
| DTBench | 89.1% | 96.5% |
| LMCA | 48.5% | 53.9% |
| Epoch Capabilities Index | 156.39 | 156.75 |
| ARC-AGI-2 | 59.5% | — |
| SimpleBench | 46.8% | — |
| Kagi LLM Benchmark | 49.1% | — |
| ARC-AGI-1 | 88% | — |
| Surface Evolver Bench | 61.9% | — |
| Bench to the Future 3 | — | 0.14 |
Math GPT-5.6 Luna leads
GPT-5.6 Luna: 77.7 (#14), Muse Spark 1.3: 73.1 (#21)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 82.1% | 74.4% |
| FrontierMath Tier 4 | 61% | 46.3% |
| OTIS Mock AIME 2024-2025 | 98.3% | 99.2% |
| ProofBench | 60% | 58% |
| LMArena Math | 1458 | 1494 |
Knowledge GPT-5.6 Luna leads
GPT-5.6 Luna: 58.5 (#34), Muse Spark 1.3: 42.6 (#95)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1478 | 1516 |
| GPQA Diamond | 91.6% | — |
| SimpleQA Verified | 41% | — |
Multimodal Too close to call
GPT-5.6 Luna: 42.7 (#28), Muse Spark 1.3: 43.7 (#22)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | 1258 | 1309 |
| LMArena Document | 1457 | 1471 |
| Blueprint-Bench 2 | 22.6% | — |
| Furniture Assembly | 42.5% | — |
Multilingual Muse Spark 1.3 leads
GPT-5.6 Luna: 52.8 (#78), Muse Spark 1.3: 57.4 (#8)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1417 | 1481 |
| LMArena Chinese | 1470 | 1529 |
| LMArena French | 1456 | 1524 |
| LMArena German | 1454 | 1515 |
| LMArena Japanese | 1411 | 1474 |
| LMArena Korean | 1415 | 1501 |
| LMArena Russian | 1428 | 1490 |
| LMArena Spanish | 1448 | 1490 |
Instruction Following Muse Spark 1.3 leads
GPT-5.6 Luna: 75.6 (#57), Muse Spark 1.3: 77.5 (#22)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1437 | 1477 |
Long Context Muse Spark 1.3 leads
GPT-5.6 Luna: 43.9 (#82), Muse Spark 1.3: 45.6 (#32)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1436 | 1488 |
Writing & Preference Muse Spark 1.3 leads
GPT-5.6 Luna: 68.0 (#29), Muse Spark 1.3: 73.6 (#9)
| Benchmark | GPT-5.6 Luna | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1431 | 1490 |
| LMArena Creative Writing | 1396 | 1455 |
| EQ-Bench Creative Writing | 1829 | 1906 |
| LMArena Multi-Turn | 1434 | 1482 |
| EQ-Bench 4 | 1156 | — |
Frequently asked questions
Is GPT-5.6 Luna better than Muse Spark 1.3?
GPT-5.6 Luna and Muse Spark 1.3 score almost the same on the Noometry Index (54.6 vs 54.8), so choose on price, context window or the category you care about most.
Which is cheaper, GPT-5.6 Luna or Muse Spark 1.3?
GPT-5.6 Luna is cheaper. It lists at $0.20 per million input tokens and $1.20 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is GPT-5.6 Luna or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 54.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Luna does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-5.6 Luna and Muse Spark 1.3 share?
36 benchmarks have published results for both models. GPT-5.6 Luna has 52 scored results on Noometry and Muse Spark 1.3 has 37.