Model Comparison
MiniMax M2 vs Muse Spark 1.1Which is better in 2026?
Muse Spark 1.1 significantly outperforms across most benchmarks. MiniMax M2 is 3.8x cheaper per token.
Verdict: MiniMax M2 vs Muse Spark 1.1 — which is better?
MiniMax M2 (by MiniMax) and Muse Spark 1.1 (by Meta) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
MiniMax M2 outperforms in 0 benchmarks, while Muse Spark 1.1 is better at 1 benchmark (Humanity's Last Exam). Muse Spark 1.1 significantly outperforms across most benchmarks.
On price, MiniMax M2 is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.1 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose MiniMax M2 if…
- cost matters — it's about 3.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Muse Spark 1.1 if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Performance Benchmarks
Comparative analysis across standard metrics
MiniMax M2 outperforms in 0 benchmarks, while Muse Spark 1.1 is better at 1 benchmark (Humanity's Last Exam).
Muse Spark 1.1 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, MiniMax M2 ($0.30/1M tokens) is 4.2x cheaper than Muse Spark 1.1 ($1.25/1M tokens).
For output processing, MiniMax M2 ($1.20/1M tokens) is 3.5x cheaper than Muse Spark 1.1 ($4.25/1M tokens).
In conclusion, Muse Spark 1.1 is more expensive than MiniMax M2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.1 accepts 1,048,576 input tokens compared to MiniMax M2's 1,000,000 tokens. MiniMax M2 can generate longer responses up to 1,000,000 tokens, while Muse Spark 1.1 is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Muse Spark 1.1 supports multimodal inputs, whereas MiniMax M2 does not.
Muse Spark 1.1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
MiniMax M2
Muse Spark 1.1
License
Usage and distribution terms
MiniMax M2 is licensed under MIT, while Muse Spark 1.1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
MiniMax M2 was released on 2025-10-27, while Muse Spark 1.1 was released on 2026-07-09.
Muse Spark 1.1 is 9 months newer than MiniMax M2.
Oct 27, 2025
9 months ago
Jul 9, 2026
2 weeks ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
MiniMax M2 is available from MiniMax, Novita. Muse Spark 1.1 is available from Meta Model API.
MiniMax M2
Muse Spark 1.1
Outputs Comparison
Key Takeaways
MiniMax M2
View detailsMiniMax
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against MiniMax M2 and Muse Spark 1.1 side-by-side, then vote on the output you prefer.
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FAQ
Common questions about MiniMax M2 vs Muse Spark 1.1.