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 altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
# Run inference directly in the terminal:
llama cli -hf altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
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 altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
# Run inference directly in the terminal:
./llama-cli -hf altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
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 altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
Use Docker
docker model run hf.co/altomek/Qwen3.5-35B-A3B-XXL-GGUF:BF16
Quick Links

Qwen3.5-35B-A3B

XXL GGUF quant of https://huggingface.co/Qwen/Qwen3.5-35B-A3B

MoE models degrade fast in qunats, tried to keep all important layers in BF16.

REUPLOAD with even more BF16 and Q4 & Q5 - Q6 was a little to big.

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GGUF
Model size
35B params
Architecture
qwen35moe
Hardware compatibility
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