GPT-6 Astra vs Muse Spark 1.3
GPT-6 Astra and Muse Spark 1.3 are closely matched at 60.7 and 55.3 on the LLM Stats Score. Muse Spark 1.3 is 160.0x cheaper per token.
OpenAI · Meta · Updated for 2026
Which is better?
GPT-6 Astra and Muse Spark 1.3 are closely matched on the overall LLM Stats Score at 60.7 and 55.3.
In the 3 individual benchmarks reported for both models, Muse Spark 1.3 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Muse Spark 1.3 is roughly 160.0x 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
- 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 1.3
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 160.0x 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 1.3
GPT-6 Astra outperforms in 1 benchmarks (OSWorld 2.0), while Muse Spark 1.3 is better at 2 benchmarks (AutomationBench, DeepSWE 1.1).
Muse Spark 1.3 shows notably better performance in the majority of 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 100.0x more expensive than Muse Spark 1.3 ($0.10/1M tokens).
For output processing, GPT-6 Astra ($50.00/1M tokens) is 250.0x more expensive than Muse Spark 1.3 ($0.20/1M tokens).
In conclusion, GPT-6 Astra is more expensive than Muse Spark 1.3.*
* 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 1.3's 1,048,576 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 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 1.3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-6 Astra
Muse Spark 1.3
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 2026-09-03, while Muse Spark 1.3 was released on 2026-09-02.
GPT-6 Astra is 0 month newer than Muse Spark 1.3.
Sep 3, 2026
0 days ago
1d newerSep 2, 2026
1 days ago
Knowledge Cutoff
When training data ends
GPT-6 Astra has a documented knowledge cutoff of 2026-04-30, while Muse Spark 1.3'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 1.3's cutoff date.
Apr 2026
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Provider Availability
GPT-6 Astra is available from OpenAI. Muse Spark 1.3 is available from Meta Model API.
GPT-6 Astra
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Astra and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Astra vs Muse Spark 1.3.