How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dispatchAI/Llama-3.2-3B-Instruct-mobile
# Run inference directly in the terminal:
llama cli -hf dispatchAI/Llama-3.2-3B-Instruct-mobile
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf dispatchAI/Llama-3.2-3B-Instruct-mobile
# Run inference directly in the terminal:
llama cli -hf dispatchAI/Llama-3.2-3B-Instruct-mobile
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 dispatchAI/Llama-3.2-3B-Instruct-mobile
# Run inference directly in the terminal:
./llama-cli -hf dispatchAI/Llama-3.2-3B-Instruct-mobile
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 dispatchAI/Llama-3.2-3B-Instruct-mobile
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dispatchAI/Llama-3.2-3B-Instruct-mobile
Use Docker
docker model run hf.co/dispatchAI/Llama-3.2-3B-Instruct-mobile
Quick Links

Llama 3.2 3B Instruct - Mobile (GGUF)

The sweet spot between size and capability. When 1B isn't enough but you still need mobile compatibility.

Property Value
Parameters 3.2 billion
Size ~2.1 GB
Speed ~16 tok/s (S20 FE CPU)
Quality Retention ~96%

Best For

  • Complex reasoning on mobile (better than 1B)
  • Long-form content generation
  • Multi-turn conversations with context
  • Advanced RAG pipelines
  • Research assistant applications
Downloads last month
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GGUF
Model size
3B params
Architecture
llama
Hardware compatibility
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