feat(ana-ml2): replace Qwen3.5-9B vision with Qwen3.6-35B-A3B FP8 on GPU 1

Retire qwen35-vl (Qwen3.5-9B); add qwen36-vl serving the official FP8
Qwen3.6-35B-A3B vision MoE on :8007 under its TRUE name only — no alias.
qwen3.5-9b-fp8 is killed at vLLM AND the litellm gateway (404/400); a model is
never served under a prior model's name. Consumer (comfy-dev/arbo) notified +
migrated; arbo vkeys flipped to all-proxy-models; shared all-agents-local key
repointed to qwen3.6-35b-a3b.

GPU-1 rebalance for the heavier FP8 weights (~34 GB): granite 0.35->0.24 /
131K->64K, embed/rerank 0.05->0.03 (reclaimed util-reservation waste). Verified:
vision correct, 20-concurrent/endpoint load test = no OOM (~7.5 GB headroom).

Drop the llama-swap qwen3.5-9b GPU-0 pin (GPU 0 freed for the creative-writing
hot-swap card). NVFP4 was the lighter fit (~21 GB) but its vLLM ModelOpt-MoE
loader is broken (KeyError w2_input_scale / lm_head.input_scale, vllm #44081);
revisit when fixed.

stacks/qwen36-vl/.env.example

@@ -0,0 +1,34 @@
+# Qwen3.6-35B-A3B VL (official FP8) on ana-ml2 — copy to .env on the host and fill.
+# Real .env lives on ana-ml2 at /opt/docker/compose/qwen36-vl/.env (gitignored).
+#
+# Replaces qwen35-vl (Qwen3.5-9B) 2026-06-14. See compose.yaml header for the
+# FP8-over-NVFP4 rationale (vLLM NVFP4 MoE loader broken, #44081) and why this
+# uses plain :latest with NO --quantization (pre-quantized checkpoint; a forced
+# flag would noise-quantize the vision tower like the old qwen35-vl).
+
+# :latest is fine — the official FP8 checkpoint loads + serves vision correctly
+# on 0.19.1 (validated 2026-06-14). NO pinned nightly digest needed.
+QWEN_IMAGE=vllm/vllm-openai:latest
+
+QWEN_CONTAINER_NAME=vllm-qwen36
+QWEN_MODEL=Qwen/Qwen3.6-35B-A3B-FP8
+QWEN_PORT=8007
+
+# GPU 1 = shared with the granite summarizer + embed/rerank/reward trio.
+# GPU 0 is kept free for the llama-swap creative-writing hot-swap card.
+QWEN_GPU_ID=1
+
+# util 0.42 (~40 GB) — official FP8 weights load in ~34.2 GiB; 0.42 covers
+# weights + CUDA-graph + a generous KV pool. Hybrid attn (10 of 40 layers full-
+# attn, ~10 KB/tok KV) makes long context nearly free, so max-len is generous.
+# Budget (2026-06-14): qwen36 0.42 + granite 0.28 + trio 0.20 = 0.90 total,
+# ~10 GB graph headroom. Bring qwen36 up LAST so capture sees the free room.
+QWEN_GPU_MEM_UTIL=0.42
+QWEN_MAX_MODEL_LEN=131072
+# Sampler-warmup OOM guard on the shared GPU (248K vocab × default 1024 seqs is
+# a huge transient). 32 is plenty for a vision endpoint.
+QWEN_MAX_NUM_SEQS=32
+
+# Optional
+HF_TOKEN=
+API_KEY=