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 inclusionAI/Ling-3.0-tiny-GGUF:
# Run inference directly in the terminal:
llama cli -hf inclusionAI/Ling-3.0-tiny-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf inclusionAI/Ling-3.0-tiny-GGUF:
# Run inference directly in the terminal:
llama cli -hf inclusionAI/Ling-3.0-tiny-GGUF:
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf inclusionAI/Ling-3.0-tiny-GGUF:
# Run inference directly in the terminal:
./build/bin/llama cli -hf inclusionAI/Ling-3.0-tiny-GGUF:
Use Docker
docker model run hf.co/inclusionAI/Ling-3.0-tiny-GGUF:
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Ling-3.0-tiny-GGUF

Ling-3.0-tiny is a lightweight hybrid reasoning MoE model with 7.9B total parameters and only 1.3B activated parameters per token. It is designed to deliver strong reasoning and agentic capabilities at low inference cost, making advanced model capabilities more accessible for local and resource-constrained deployment.

Find more details in the original model card: https://huggingface.co/inclusionAI/Ling-3.0-tiny

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