Initial vLLM Qwen3.6-35B-A3B-FP8 serving with CPU expert offloading

vllm-qwen36.sh

@@ -0,0 +1,33 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+# Qwen3.6-35B-A3B-FP8 vLLM serving script for dankserver
+# CPU expert offloading to fit MoE model on 24GB RTX 3090
+
+MODEL="Qwen/Qwen3.6-35B-A3B-FP8"
+DRAFT_MODEL="/home/dank/.cache/huggingface/models/Qwen3.6-35B-A3B-DFlash"
+PORT=8001
+HOST="0.0.0.0"
+
+exec docker run --rm --name vllm-qwen36 \
+    --gpus all \
+    --privileged \
+    --ipc=host \
+    -p "${PORT}:${PORT}" \
+    -e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \
+    -v /home/dank/.cache/huggingface:/root/.cache/huggingface \
+    docker.io/vllm/vllm-openai:nightly \
+    "${MODEL}" \
+    --port "${PORT}" \
+    --host "${HOST}" \
+    --kv-cache-dtype fp8 \
+    --gpu-memory-utilization 0.95 \
+    --max-num-seqs 3 \
+    --max-model-len 16384 \
+    --max-num-batched-tokens 4096 \
+    --trust-remote-code \
+    --cpu-offload-gb 30 \
+    --cpu-offload-params "experts" \
+    --enable-chunked-prefill \
+    --enable-prefix-caching \
+    --enforce-eager