Muse Wonder vs Phi-3.5-MoE-instruct
Muse Wonder leads the LLM Stats Score 47.9 to 1.9.
Meta · Microsoft · Updated for 2026
Which is better?
Muse Wonder leads the overall LLM Stats Score 47.9 to 1.9, ranking #29 overall.
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 and coding — it leads those capability indexes
- you want the most recent training data — it shipped Oct 2026
Choose Phi-3.5-MoE-instruct
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
16 reported for Muse Wonder · 31 for Phi-3.5-MoE-instruct
Muse Wonder and Phi-3.5-MoE-instructdon'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
Context Window
Maximum input and output token capacity
Only Muse Wonder specifies input context (1,048,576 tokens).
Input capabilities
Documented input modalities across available providers
Muse Wonder supports multimodal inputs, whereas Phi-3.5-MoE-instruct does not.
Muse Wonder can handle both text and other forms of data like images, making it suitable for multimodal applications.
Muse Wonder
Phi-3.5-MoE-instruct
License
Usage and distribution terms
Muse Wonder is licensed under a proprietary license, while Phi-3.5-MoE-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Muse Wonder was released on 2026-10-12, while Phi-3.5-MoE-instruct was released on 2024-08-23.
Muse Wonder is 26 months newer than Phi-3.5-MoE-instruct.
Oct 12, 2026
1 days ago
2.1yr newerAug 23, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Muse Wonder and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about Muse Wonder vs Phi-3.5-MoE-instruct.