Model comparison
GPT-6 Astra vs Muse Spark 1.2
GPT-6 Astra is the stronger model overall, scoring 70.8 to 50.3 on the Noometry Index. Muse Spark 1.2 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 . 30 shared benchmarks.
MetaSummary
- They share 30 benchmarks with published results for both. GPT-6 Astra scores higher in 7 categories and Muse Spark 1.2 in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Astra leads 93.5 to 46.4.
- The biggest single-benchmark swing is ProofBench: 99% for GPT-6 Astra and 43% for Muse Spark 1.2.
- Muse Spark 1.2 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 1.2 | |
|---|---|---|
| Provider | OpenAI | Meta |
| Noometry Index | 70.8 | 50.3 |
| Released | 2026-09-03 | 2026-08-05 |
| 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 | 31 |
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Category by category
Coding GPT-6 Astra leads
GPT-6 Astra: 73.7 (#2), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| DeepSWE | 74.1% | 54.9% |
| LMArena WebDev | 1786 | 1533 |
| FrontierSWE | 65.5% | 12% |
| SciCode | 56.5% | 56.4% |
| WeirdML | 93.6% | 60.3% |
| LMArena Coding | 1487 | 1495 |
| FrontierCode | 53.3% | — |
| GSO | 79.4% | — |
| MirrorCode | 46.7% | — |
| ALE-Bench | 2,951 | — |
Agentic & Tool Use GPT-6 Astra leads
GPT-6 Astra: 52.9 (#3), Muse Spark 1.2: 29.4 (#87)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | 64.7% | 36.4% |
| GDP.pdf | 34.2% | 16% |
| Remote Labor Index | 20.8% | — |
| BALROG | 68.3% | — |
| Vending-Bench 2 | 15,515 | — |
Reasoning GPT-6 Astra leads
GPT-6 Astra: 85.1 (#1), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| NYT Connections (extended) | 98.1% | 79.2% |
| CritPt | 31.7% | 17.7% |
| LMArena Hard Prompts | 1462 | 1486 |
| DTBench | 97.3% | 94.7% |
| LMCA | 64.4% | 48.4% |
| Epoch Capabilities Index | 166.45 | 154.87 |
| ARC-AGI-2 | 95% | — |
| SimpleBench | — | 74.5% |
| ARC-AGI-1 | 98.5% | — |
| Chess Puzzles | 72% | — |
| EBR-Bench | 76.2% | — |
| Mystery Game Puzzles | 84% | — |
| Bench to the Future 3 | 0.14 | — |
Math GPT-6 Astra leads
GPT-6 Astra: 93.5 (#2), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| ProofBench | 99% | 43% |
| LMArena Math | 1465 | 1471 |
| 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 1.2: 54.1 (#53)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 75.6% | 60.3% |
| LMArena Expert | 1483 | 1480 |
| 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 1.2: 43.4 (#25)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | 1281 | 1305 |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
| LMArena Document | 1468 | — |
Multilingual Muse Spark 1.2 leads
GPT-6 Astra: 53.7 (#61), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1430 | 1478 |
| LMArena Chinese | 1484 | 1511 |
| LMArena French | 1456 | 1513 |
| LMArena Russian | 1436 | 1487 |
| LMArena Spanish | 1407 | 1498 |
| LMArena German | 1440 | — |
| LMArena Japanese | 1379 | — |
| LMArena Korean | 1426 | — |
Instruction Following Too close to call
GPT-6 Astra: 76.3 (#44), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1450 | 1461 |
Long Context Too close to call
GPT-6 Astra: 44.5 (#62), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1456 | 1475 |
Writing & Preference GPT-6 Astra leads
GPT-6 Astra: 75.3 (#7), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GPT-6 Astra | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1441 | 1482 |
| LMArena Creative Writing | 1418 | 1449 |
| EQ-Bench Creative Writing | 2173 | 1840 |
| LMArena Multi-Turn | 1448 | 1494 |
Frequently asked questions
Is GPT-6 Astra better than Muse Spark 1.2?
GPT-6 Astra is the stronger model overall, scoring 70.8 to 50.3 on the Noometry Index. Muse Spark 1.2 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 1.2?
Muse Spark 1.2 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 1.2 better for coding?
GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 49.2 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 1.2 share?
30 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and Muse Spark 1.2 has 31.