Microsoft
Phi-tiny-MoE is a lightweight Mixture of Experts (MoE) model with 3.8B total parameters and 1.1B activated parameters. It is compressed and distilled from the base model shared by Phi-3.5-MoE and GRIN-MoE using the SlimMoE approach, then post-trained via supervised fine-tuning and direct preference optimization for...
Running this yourself: consumer gpu should be enough.
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35.1
Quality Score
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Arena ELO
4B
Parameters
4K
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
16 of 22 public signals
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126.4K
Downloads
43
Likes
Jun 2025
Released
5/5 signals
2/4 signals
3/5 signals
3/4 signals
3/4 signals
Parameters
4B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources