Muse Wonder vs Pixtral Large
Muse Wonder leads the LLM Stats Score 47.9 to 11.8. Pixtral Large is 2.7x cheaper per token.
Meta · Mistral AI · Updated for 2026
Which is better?
Muse Wonder leads the overall LLM Stats Score 47.9 to 11.8, ranking #29 overall.
On price, Pixtral Large is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Wonder also accepts a larger context window (1,048,576 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 Muse Wonder
- overall performance matters — it scores 47.9 and ranks #29 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose Pixtral Large
- cost matters — it's about 2.7x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for Muse Wonder · 7 for Pixtral Large
Muse Wonder and Pixtral Largedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Muse Wonder ($4.00/1M tokens) is 2.0x more expensive than Pixtral Large ($2.00/1M tokens).
For output processing, Muse Wonder ($20.00/1M tokens) is 3.3x more expensive than Pixtral Large ($6.00/1M tokens).
In conclusion, Muse Wonder is more expensive than Pixtral Large.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Wonder accepts 1,048,576 input tokens compared to Pixtral Large's 128,000 tokens. Only Pixtral Large specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both Muse Wonder and Pixtral Large support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Muse Wonder
Pixtral Large
License
Usage and distribution terms
Muse Wonder is licensed under a proprietary license, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Mistral Research License (MRL) for research; Mistral Commercial License for commercial use
Open weights
Release Timeline
When each model was launched
Muse Wonder was released on 2026-10-12, while Pixtral Large was released on 2024-11-18.
Muse Wonder is 23 months newer than Pixtral Large.
Oct 12, 2026
0 days ago
1.9yr newerNov 18, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Muse Wonder is available from Meta Model API. Pixtral Large is available from Mistral AI.
Muse Wonder
Pixtral Large
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Wonder and Pixtral Large side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Wonder vs Pixtral Large.