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
Download history
daily snapshots · 10 days920 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.
| File | Quant | Size | Est. VRAM | Verdict 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 -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"
}
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
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