microsoft / text-generation updated 7 months ago

Phi-tiny-MoE-instruct

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 instruction following and safety. The model is trained on Phi-3 synthetic data and filtered public docu...

Params
3.8 B
Context
4,096
Downloads 30d
907 K
Likes
42
Commercial use: allowed mit Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days
920 K875 K
Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
model.safetensors bf16 7.5 GB 9.3 GB ✅ Runs comfortably
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · curl · api/v1
$ curl -s https://aimodelscomparison.com/api/v1/models/phi-tiny-moe-instruct
{
  "hf_id": "microsoft/Phi-tiny-MoE-instruct",
  "params_b": 3.76,
  "context_length": 4096,
  "license": { "id": "mit", "commercial": "yes" },
  "downloads_30d": 906711,
  "vram_estimates": [
    { "quant": "bf16", "gb": 9.3 }
  ],
  "updated_at": "2026-07-28T18:03:44Z"
}
est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture
PhiMoEForCausalLM
Parameters
3.8 B
Tensor type
BF16
Context length
4,096
Vocabulary
32,064
Layers / heads
32 / 16
Licence
mit
First seen on the Hub
2025-06-23
Training datasets
undisclosed
Added to our catalog
2026-07-28