microsoft / text-generation updated 7 months ago

Phi-4-mini-instruct

Name: Phi-4-mini-instruct
Author: microsoft

🎉Phi-4: [mini-reasoning reasoning] [multimodal-instruct onnx]; [mini-instruct onnx]

Params

3.8 B

Context

131,072

Downloads 30d

455 K

Likes

804

Commercial use: allowed mit Not gated SAFETENSORS 24 languages View on Hugging Face ↗

Download history

daily snapshots · 10 days

471 K427 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	7.7 GB	9.5 GB	✅ Runs comfortably
model.safetensors (bf16, full)	bf16 + 128K ctx	7.7 GB	18.2 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-4-mini-instruct
{
  "hf_id": "microsoft/Phi-4-mini-instruct",
  "params_b": 3.84,
  "context_length": 131072,
  "license": { "id": "mit", "commercial": "yes" },
  "downloads_30d": 455062,
  "vram_estimates": [
    { "quant": "bf16", "gb": 9.5 }
  ],
  "updated_at": "2026-07-28T18:05:37Z"
}

est. VRAM —on RTX 4090 · 24 GBJSON API →

Specifications

Architecture: Phi3ForCausalLM
Parameters: 3.8 B
Tensor type: BF16
Context length: 131,072
Vocabulary: 200,064
Layers / heads: 32 / 24
Licence: mit
First seen on the Hub: 2025-02-19
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Compare with

Qwen3-8B 16.3 M Qwen2.5-1.5B-Instruct 14.0 M Qwen2.5-7B-Instruct 12.1 M Qwen3-1.7B 7.8 M Qwen2.5-3B-Instruct 6.0 M Qwen3-4B 4.6 M

Appears in

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