How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf llmware/phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf llmware/phi-4-mini-gguf:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf llmware/phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf llmware/phi-4-mini-gguf:Q4_K_M
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf llmware/phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf llmware/phi-4-mini-gguf:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf llmware/phi-4-mini-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf llmware/phi-4-mini-gguf:Q4_K_M
Use Docker
docker model run hf.co/llmware/phi-4-mini-gguf:Q4_K_M
Quick Links

phi-4-mini-instruct-gguf

phi-4-mini-instruct-gguf is a GGUF Q4_K_M int4 quantized version of phi-4-mini-instruct, providing a very fast inference implementation, optimized for AI PCs.

This model will run on an AI PC with at least 16 GB of memory.

Model Description

  • Developed by: Microsoft
  • Model type: phi-4-mini
  • Parameters: 4 billion
  • Model Parent: Microsoft/Phi-4-Mini-Instruct
  • Language(s) (NLP): English
  • License: Apache 2.0
  • Uses: Chat, general-purpose LLM
  • Quantization: int4

Model Card Contact

llmware on github

llmware on hf

llmware website

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GGUF
Model size
4B params
Architecture
phi3
Hardware compatibility
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