How to use from
llama.cppInstall from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Ilya626/MoonGem-MTP:Q4_K_M# Run inference directly in the terminal:
llama cli -hf Ilya626/MoonGem-MTP:Q4_K_MUse 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 Ilya626/MoonGem-MTP:Q4_K_M# Run inference directly in the terminal:
./llama-cli -hf Ilya626/MoonGem-MTP:Q4_K_MBuild 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 Ilya626/MoonGem-MTP:Q4_K_M# Run inference directly in the terminal:
./build/bin/llama-cli -hf Ilya626/MoonGem-MTP:Q4_K_MUse Docker
docker model run hf.co/Ilya626/MoonGem-MTP:Q4_K_MQuick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
llama.cpp startup
Use a llama.cpp build supporting Gemma 4 Assistant draft-mtp.
Download the Assistant GGUF from this repository and your MoonGem-31B target GGUF.
Replace the three paths below with your own paths, then run:
LLAMA_SERVER="/path/to/llama-server"
TARGET_GGUF="/path/to/MoonGem-31B.gguf"
ASSISTANT_GGUF="/path/to/MoonGem-MTP-Assistant-Q4_K_M.gguf"
"$LLAMA_SERVER" \
--model "$TARGET_GGUF" \
--model-draft "$ASSISTANT_GGUF" \
--spec-type draft-mtp \
--spec-draft-n-max 4 \
--spec-draft-p-min 0 \
--n-gpu-layers 99 \
--n-gpu-layers-draft 99 \
--ctx-size 8192 \
--jinja \
--temp 0.9 --top-p 0.95 --top-k 64 --min-p 0.02 \
--host 127.0.0.1 --port 8080
The Assistant GGUF already includes the LoRA; no additional --lora flag is needed.
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Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf Ilya626/MoonGem-MTP:Q4_K_M# Run inference directly in the terminal: llama cli -hf Ilya626/MoonGem-MTP:Q4_K_M