Pyyan / Compare / Muse Spark 1.3 vs GPT-6 Astra
Muse Spark 1.3 vs GPT-6 Astra
2 of 5Language Models · verified 5 Sept 2026
Muse Spark 1.3Metacurrent
GPT-6 AstraOpenAIcurrent| Specification | Muse Spark 1.3 | GPT-6 Astra |
|---|---|---|
| Summary | A quarter fewer tokens than 1.2 for the same work, which is the figure on the bill. | Saturates three of the benchmarks it reports, and ships disabled for enterprise. |
| Context | 1M | 1.05M |
| Input ($/Mtok) | $1.25 | $10 |
| Output ($/Mtok) | $4.25 | $50 |
| Licence | Proprietary | Proprietary |
| Max output | Not published | 128K |
| Parameters | Not published | Not published |
| Released | 2 Sep 2026 | 3 Sep 2026 |
| Model ID | muse-spark-1.3 | gpt-6-astra |
| Category | Language Models | Language Models |
| Official | — | — |
Highlighted rows are where these differ.
Muse Spark 1.3
- About 20% fewer tool calls and 25% fewer tokens than 1.2 to reach the same result
- 75.4 on DeepSWE v1.1 and 98.5 on MRCR long context between 256K and 512K
- A Contributor tier costs $0.10 in and $0.20 out for the same model, in exchange for letting Meta train on your prompts
Best for long running agentic coding.
GPT-6 Astra
- 97.6% on FrontierMath Tier 4, 99.9% on ARC-AGI-3 and 100% on ExploitBench
- Above 272K input tokens the whole request reprices: input and cache at 2x, output at 1.5x
- Rolls out to OpenAI's Daybreak cyber programme first, and arrives switched off for enterprise
Best for hard reasoning and computer use.