docker run -d --name gemma4-dflash \
  --gpus all --network host --ipc host \
  --ulimit memlock=-1 --ulimit stack=67108864 \
  -v "$HOME/.cache/huggingface:/root/.cache/huggingface" \
  -e PORT=8000 \
  -e SERVED_MODEL_NAME=google/gemma-4-31B-it-vllm-fp8-dflash-16k \
  -e HF_TOKEN=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 \
  -e VLLM_DISABLE_COMPILE_CACHE=1 \
  --entrypoint "" \
  gemma4-dflash:arm64 \
  bash -c "
python3 /opt/gemma4-dflash-spark-vllm/scripts/patch_vllm_gb10_gemma4_dflash_runtime.py
exec vllm serve google/gemma-4-31B-it \
  --host 0.0.0.0 \
  --port 8000 \
  --served-model-name google/gemma-4-31B-it-vllm-fp8-dflash-16k \
  --trust-remote-code \
  --max-model-len 16384 \
  --gpu-memory-utilization 0.80 \
  --quantization fp8 \
  --tensor-parallel-size 1 \
  --max-num-batched-tokens 16384 \
  --enforce-eager \
  --speculative-config '{"model":"RedHatAI/gemma-4-31B-it-speculator.dflash","num_speculative_tokens":8,"method":"dflash"}' \
  --limit-mm-per-prompt '{"image":0,"video":0}' \
  --enable-auto-tool-choice \
  --tool-call-parser hermes
"
