GPT-6 Astra vs Muse Spark 1.1
GPT-6 Astra leads the LLM Stats Score 60.3 to 49.7. Muse Spark 1.1 is 10.0x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-6 Astra leads the overall LLM Stats Score 60.3 to 49.7, ranking #1 overall.
In the 1 individual benchmarks reported for both models, GPT-6 Astra wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Spark 1.1 is roughly 10.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Astra also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Astra
- overall performance matters — it scores 60.3 and ranks #1 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Muse Spark 1.1
- cost matters — it's about 10.0x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for GPT-6 Astra · 11 for Muse Spark 1.1
GPT-6 Astra outperforms in 1 benchmarks (DeepSWE 1.1), while Muse Spark 1.1 is better at 0 benchmarks.
GPT-6 Astra significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Astra ($10.00/1M tokens) is 8.0x more expensive than Muse Spark 1.1 ($1.25/1M tokens).
For output processing, GPT-6 Astra ($50.00/1M tokens) is 11.8x more expensive than Muse Spark 1.1 ($4.25/1M tokens).
In conclusion, GPT-6 Astra is more expensive than Muse Spark 1.1.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Astra accepts 1,050,000 input tokens compared to Muse Spark 1.1's 1,048,576 tokens. Muse Spark 1.1 can generate longer responses up to 131,072 tokens, while GPT-6 Astra is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-6 Astra and Muse Spark 1.1 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Astra
Muse Spark 1.1
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-6 Astra was released on 2026-09-04, while Muse Spark 1.1 was released on 2026-07-09.
GPT-6 Astra is 2 months newer than Muse Spark 1.1.
Sep 4, 2026
4 days ago
1mo newerJul 9, 2026
2 months ago
Knowledge Cutoff
When training data ends
GPT-6 Astra has a documented knowledge cutoff of 2026-04-30, while Muse Spark 1.1's cutoff date is not specified.
We can confirm GPT-6 Astra's training data extends to 2026-04-30, but cannot make a direct comparison without Muse Spark 1.1's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Astra is available from OpenAI. Muse Spark 1.1 is available from Meta Model API.
GPT-6 Astra
Muse Spark 1.1
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Astra and Muse Spark 1.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Astra vs Muse Spark 1.1.