microsoft / text-generation updated 7 months ago

Phi-3-mini-128k-instruct

The Phi-3-Mini-128K-Instruct is a 3.8 billion-parameter, lightweight, state-of-the-art open model trained using the Phi-3 datasets. This dataset includes both synthetic data and filtered publicly available website data, with an emphasis on high-quality and reasoning-dense properties. The model belongs to the Phi-3 family with the Mini version in two variants 4K and 128K which is the context length (in tokens) that it...

Params
3.8 B
Context
131,072
Downloads 30d
249 K
Likes
1,704
Commercial use: allowed mit Not gated SAFETENSORS 1 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days
249 K243 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 7.6 GB 9.5 GB ✅ Runs comfortably
model.safetensors (bf16, full) bf16 + 128K ctx 7.6 GB 18.1 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-3-mini-128k-instruct
{
  "hf_id": "microsoft/Phi-3-mini-128k-instruct",
  "params_b": 3.82,
  "context_length": 131072,
  "license": { "id": "mit", "commercial": "yes" },
  "downloads_30d": 249193,
  "vram_estimates": [
    { "quant": "bf16", "gb": 9.5 }
  ],
  "updated_at": "2026-07-28T18:07:17Z"
}
est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture
Phi3ForCausalLM
Parameters
3.8 B
Tensor type
BF16
Context length
131,072
Vocabulary
32,064
Layers / heads
32 / 32
Licence
mit
First seen on the Hub
2024-04-22
Training datasets
undisclosed
Added to our catalog
2026-07-28