Model comparison
GPT-5.1 vs Muse Spark 1.1
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 48.8 on the Noometry Index.
Last verified . 27 shared benchmarks.
MetaSummary
- They share 27 benchmarks with published results for both. GPT-5.1 scores higher in 4 categories and Muse Spark 1.1 in 6 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Muse Spark 1.1 leads 73.6 to 64.7.
- The biggest single-benchmark swing is SciCode: 43.3% for GPT-5.1 and 58.8% for Muse Spark 1.1.
- Muse Spark 1.1 is cheaper at $1.25 / $4.25 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- Muse Spark 1.1 accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5.1 | Muse Spark 1.1 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 48.8 | 49.9 |
| Released | 2025-11-13 | 2026-04-08 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $1.25 | $1.25 |
| Output $ / M tokens | $10 | $4.25 |
| Results tracked | 63 | 36 |
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Category by category
Coding Muse Spark 1.1 leads
GPT-5.1: 46.9 (#59), Muse Spark 1.1: 50.8 (#38)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena WebDev | 1395 | 1542 |
| SciCode | 43.3% | 58.8% |
| LMArena Coding | 1454 | 1497 |
| SWE-bench Verified | 68% | — |
| DeepSWE | — | 53.3% |
| SWE-bench Verified (bash only) | 66% | — |
| GSO | 13.7% | — |
| WeirdML | 60.8% | — |
| LiveBench Coding | 72.5% | — |
| ALE-Bench | 1,192 | — |
Agentic & Tool Use Muse Spark 1.1 leads
GPT-5.1: 32.5 (#55), Muse Spark 1.1: 33.9 (#45)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| Vending-Bench 2 | 1,473 | 6,520 |
| Terminal-Bench | 47.6% | — |
| τ²-bench Banking | — | 40.5% |
| DeepResearch Bench | 42.8% | — |
| GBAEval | — | 7.9% |
| GDP.pdf | — | 15% |
| LMArena Search | 1199 | — |
Reasoning Muse Spark 1.1 leads
GPT-5.1: 39.9 (#50), Muse Spark 1.1: 45.9 (#41)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| CritPt | 4.9% | 15.1% |
| LMArena Hard Prompts | 1457 | 1486 |
| DTBench | 90.1% | 94.4% |
| LMCA | 43.9% | 49.9% |
| Epoch Capabilities Index | 149.66 | 154.32 |
| ARC-AGI-2 | 17.6% | — |
| SimpleBench | 53.2% | — |
| NYT Connections (extended) | — | 84.9% |
| ARC-AGI-1 | 72.8% | — |
| Chess Puzzles | 32% | — |
| EnigmaEval | 11.2% | — |
| LiveBench Reasoning | 95.8% | — |
| Mystery Game Puzzles | 19% | — |
| LiveBench Data Analysis | 72.1% | — |
| Surface Evolver Bench | — | 52.5% |
| ForecastBench | 58.1 | — |
| LiveBench | 78.8% | — |
Math GPT-5.1 leads
GPT-5.1: 50.3 (#45), Muse Spark 1.1: 44.0 (#67)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena Math | 1446 | 1477 |
| OTIS Mock AIME 2024-2025 | 88.6% | — |
| ProofBench | — | 39% |
| Omni-MATH | 46.4% | — |
| LiveBench Math | 94.5% | — |
| FrontierMath (Feb 2025 set) | 31% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge Muse Spark 1.1 leads
GPT-5.1: 50.5 (#65), Muse Spark 1.1: 52.8 (#55)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| SimpleQA Verified | 48% | 57.8% |
| LMArena Expert | 1470 | 1480 |
| GPQA Diamond | 87.6% | — |
| Humanity's Last Exam | 23.7% | — |
| MMLU-Pro | 57.9% | — |
| Vectara Hallucination Rate | 10.9% | — |
| GPQA (HELM) | 44.2% | — |
Multimodal GPT-5.1 leads
GPT-5.1: 44.0 (#17), Muse Spark 1.1: 41.9 (#28)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | 1250 | 1292 |
| LMArena Document | 1403 | 1465 |
| VPCT | 58.7% | — |
Multilingual Muse Spark 1.1 leads
GPT-5.1: 54.0 (#51), Muse Spark 1.1: 56.8 (#16)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1431 | 1471 |
| LMArena Chinese | 1495 | 1518 |
| LMArena French | 1451 | 1494 |
| LMArena German | 1439 | 1466 |
| LMArena Japanese | 1453 | 1445 |
| LMArena Korean | 1401 | 1459 |
| LMArena Russian | 1435 | 1482 |
| LMArena Spanish | 1430 | 1471 |
Instruction Following GPT-5.1 leads
GPT-5.1: 84.0 (#1), Muse Spark 1.1: 76.8 (#36)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1442 | 1457 |
| LiveBench Instruction Following | 93.3% | — |
| IFEval | 93.5% | — |
Long Context GPT-5.1 leads
GPT-5.1: 47.6 (#14), Muse Spark 1.1: 44.8 (#55)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1448 | 1463 |
| CL-bench | 23.7% | — |
| CL-bench Life | 17.3% | — |
Writing & Preference Muse Spark 1.1 leads
GPT-5.1: 64.7 (#53), Muse Spark 1.1: 73.6 (#11)
| Benchmark | GPT-5.1 | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1443 | 1479 |
| LMArena Creative Writing | 1427 | 1440 |
| LMArena Multi-Turn | 1449 | 1484 |
| EQ-Bench Creative Writing | — | 1927 |
| WildBench | 86.3% | — |
| EQ-Bench 4 | — | 1260 |
| LiveBench Language | 80.2% | — |
Frequently asked questions
Is GPT-5.1 better than Muse Spark 1.1?
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 48.8 on the Noometry Index.
Which is cheaper, GPT-5.1 or Muse Spark 1.1?
Muse Spark 1.1 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GPT-5.1 or Muse Spark 1.1 better for coding?
Muse Spark 1.1 scores higher on coding benchmarks: 50.8 versus 46.9 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.1 does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5.1 and Muse Spark 1.1 share?
27 benchmarks have published results for both models. GPT-5.1 has 63 scored results on Noometry and Muse Spark 1.1 has 36.