Model comparison
GPT-6 Astra vs Muse Spark 1.1
GPT-6 Astra is the stronger model overall, scoring 70.8 to 49.9 on the Noometry Index. Muse Spark 1.1 costs 10× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Last verified . 33 shared benchmarks.
MetaSummary
- They share 33 benchmarks with published results for both. GPT-6 Astra scores higher in 7 categories and Muse Spark 1.1 in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 45.5.
- The biggest single-benchmark swing is ProofBench: 99% for GPT-6 Astra and 39% for Muse Spark 1.1.
- Muse Spark 1.1 is cheaper at $1.25 / $4.25 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-6 Astra | Muse Spark 1.1 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 70.8 | 49.9 |
| Released | 2026-09-03 | 2026-04-08 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 128K | 131K |
| Input $ / M tokens | $10 | $1.25 |
| Output $ / M tokens | $50 | $4.25 |
| Results tracked | 56 | 37 |
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Category by category
Coding GPT-6 Astra leads
GPT-6 Astra: 73.7 (#2), Muse Spark 1.1: 51.3 (#40)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| DeepSWE | 74.1% | 53.3% |
| LMArena WebDev | 1786 | 1542 |
| SciCode | 56.5% | 58.8% |
| LMArena Coding | 1487 | 1498 |
| FrontierCode | 53.3% | — |
| FrontierSWE | 65.5% | — |
| GSO | 79.4% | — |
| WeirdML | 93.6% | — |
| MirrorCode | 46.7% | — |
| ALE-Bench | 2,951 | — |
Agentic & Tool Use GPT-6 Astra leads
GPT-6 Astra: 52.9 (#3), Muse Spark 1.1: 30.8 (#73)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| APEX-Agents | 64.7% | 31.8% |
| GDP.pdf | 34.2% | 15% |
| Vending-Bench 2 | 15,515 | 6,520 |
| Remote Labor Index | 20.8% | — |
| τ²-bench Banking | — | 40.5% |
| BALROG | 68.3% | — |
| GBAEval | — | 7.9% |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), Muse Spark 1.1: 47.1 (#44)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| NYT Connections (extended) | 98.1% | 84.9% |
| CritPt | 31.7% | 15.1% |
| LMArena Hard Prompts | 1462 | 1486 |
| DTBench | 97.3% | 94.4% |
| LMCA | 64.4% | 49.9% |
| Epoch Capabilities Index | 166.45 | 154.21 |
| ARC-AGI-2 | 95% | — |
| ARC-AGI-1 | 98.5% | — |
| Chess Puzzles | 72% | — |
| EBR-Bench | 76.2% | — |
| Mystery Game Puzzles | 84% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | 0.14 | — |
Math GPT-6 Astra leads
GPT-6 Astra: 93.5 (#2), Muse Spark 1.1: 45.5 (#76)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| ProofBench | 99% | 39% |
| LMArena Math | 1465 | 1483 |
| FrontierMath (Tiers 1-3) | 93.7% | — |
| FrontierMath Tier 4 | 97.6% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| FrontierMath Erdős | 2.9% | — |
Knowledge GPT-6 Astra leads
GPT-6 Astra: 75.3 (#1), Muse Spark 1.1: 53.1 (#59)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| SimpleQA Verified | 75.6% | 57.8% |
| LMArena Expert | 1483 | 1478 |
| GPQA Diamond | 95.8% | — |
| Humanity's Last Exam | 54.8% | — |
| Vectara Hallucination Rate | 8.7% | — |
Multimodal GPT-6 Astra leads
GPT-6 Astra: 55.0 (#3), Muse Spark 1.1: 42.6 (#29)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | 1281 | 1293 |
| LMArena Document | 1468 | 1465 |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
Multilingual Muse Spark 1.1 leads
GPT-6 Astra: 53.7 (#61), Muse Spark 1.1: 56.7 (#17)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1430 | 1472 |
| LMArena Chinese | 1484 | 1518 |
| LMArena French | 1456 | 1494 |
| LMArena German | 1440 | 1466 |
| LMArena Japanese | 1379 | 1451 |
| LMArena Korean | 1426 | 1458 |
| LMArena Russian | 1436 | 1483 |
| LMArena Spanish | 1407 | 1464 |
Instruction Following Too close to call
GPT-6 Astra: 76.3 (#44), Muse Spark 1.1: 76.5 (#39)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1450 | 1457 |
Long Context Too close to call
GPT-6 Astra: 44.5 (#62), Muse Spark 1.1: 44.8 (#58)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1456 | 1462 |
Writing & Preference GPT-6 Astra leads
GPT-6 Astra: 75.3 (#7), Muse Spark 1.1: 73.4 (#11)
| Benchmark | GPT-6 Astra | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1441 | 1479 |
| LMArena Creative Writing | 1418 | 1437 |
| EQ-Bench Creative Writing | 2173 | 1927 |
| LMArena Multi-Turn | 1448 | 1485 |
| EQ-Bench 4 | — | 1260 |
Frequently asked questions
Is GPT-6 Astra better than Muse Spark 1.1?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 49.9 on the Noometry Index. Muse Spark 1.1 costs 10× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Astra 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-6 Astra lists at $10 and $50.
Is GPT-6 Astra or Muse Spark 1.1 better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 51.3 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Astra does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-6 Astra and Muse Spark 1.1 share?
33 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and Muse Spark 1.1 has 37.