Phi-4 Mini is Microsoft's February 2025 successor to Phi-3.5 Mini — same 3.8 B footprint but with first-class function calling, a 128K context window, and a tokenizer overhaul that doubles non-English efficiency. It beats Phi-3.5 Mini on every reasoning benchmark and approaches Phi-4 14B on math while running at ~2.3 GB VRAM at Q4_K_M. MIT licensed. The realistic deployment target: AI PCs with NPUs, mini PCs, edge servers, and even a Raspberry Pi 5 via llama.cpp. For a Lagos solo dev on a 6 GB laptop GPU, this is the local agent model that actually fits.
Phi-4 Mini 3.8B needs at minimum 2.3 GB of VRAM at Q4_K_M quantization (8.4 GB at FP16). The cheapest GPU that comfortably fits with KV-cache headroom is the Intel Arc A380 6GB (6 GB VRAM, $139 MSRP). Community benchmark submissions are open. This model fits a single consumer GPU under 48 GB, so a one-card build works.
Weights only. Add ~20-30% for KV cache at typical context lengths.
| Quant | VRAM | Quality | Notes |
|---|---|---|---|
| FP16 | 8.4 GB | Reference | Training-precision weights |
| Q8_0 | 4.2 GB | Near-lossless | 8-bit, ~0.1% perplexity hit |
| Q6_K | 3.4 GB | Very high | 6-bit, near Q8 quality |
| Q5_K_M | 2.9 GB | High | Strong middle ground |
| Q4_K_M | 2.3 GB | Balanced (recommended) | Default for local deployments |
| Q4_0 | 2.4 GB | Legacy 4-bit | Older GGUF, kept for compatibility |
| Q3_K_M | 1.8 GB | Lossy | When VRAM is very tight |
| Q2_K | 1.3 GB | Extreme | Rescue option, quality degrades visibly |
Filtered from MyAIHardware's GPU database. FP16 needs 8.4 GB; Q4_K_M needs 2.3 GB.
We don't have community benchmarks for this exact model yet.
Official weights + popular runtime tags.
ollama pull phi4-minilms get bartowski/Phi-4-mini-instruct-GGUFStep-by-step guides that use this model.
Models in a similar size or capability class.
Use these in papers, blog posts, or internal docs.
@misc{phi-4-mini-2025,
title={Phi-4 Mini 3.8B},
author={Microsoft Research},
year={2025},
url={https://huggingface.co/microsoft/Phi-4-mini-instruct}
}Microsoft Research (2025). Phi-4 Mini 3.8B [Model card]. Hugging Face. https://huggingface.co/microsoft/Phi-4-mini-instruct
Phi-4 Mini 3.8B (Phi, Microsoft Research, 2025). Available at https://huggingface.co/microsoft/Phi-4-mini-instruct.