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 Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
# Run inference directly in the terminal:
llama-cli -hf Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
# Run inference directly in the terminal:
llama-cli -hf Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
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 Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
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 Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
Use Docker
docker model run hf.co/Orion-zhen/Qwen3-30B-A3B-Instruct-2507-1M-GGUF:
Quick Links

Qwen3-30B-A3B-Instruct-2507-1M-GGUF

Scale context window up from 262144 to 1048576 (x4) using yarn.

Due to my poor limited network bandwidth, I have to pick out some quantization to upload, instead of all of them. BTW, Qwen is really good at scaling model name lol.

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