diff --git a/AGENTS.md b/AGENTS.md
index 4369c19..cd688b5 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -13,7 +13,7 @@ merge absorbed the former `vllmScripts` repo, history preserved).
 - **Dankclaw** (192.168.0.143) — AI/search/dev/observability stack (SearXNG
   via Gluetun, ComfyUI, OpenWebUI, Hermes, Gitea, Grafana, Prometheus, Loki,
   Alloy, Pi-hole) plus TWO LLM services: `frank-large` (halogen-flash-server on
-  the gfx1151 iGPU) and `frank-small` (llama.cpp on the RTX 3090). Caddy on
+  the gfx1151 iGPU) and `frank-small` (vLLM on the RTX 3090). Caddy on
   Dankclaw reverse-proxies both hosts.
 - **FrankBook-Pro** (192.168.0.112) — macOS mini running the *arr stack
   (Prowlarr, Sonarr, Radarr, Lidarr, Readarr, qBittorrent) as quadlets inside
@@ -26,7 +26,7 @@ merge absorbed the former `vllmScripts` repo, history preserved).
 |--------|---------|---------|-------|------|
 |Dankserver|`frank-medium`|mainline llama.cpp master fb27a525 (root systemd unit, gfx1201 HIP build)|ajgazin Swift-Qwen3.8-27B-Uncensored-Dynamic-MTP UD-Q8_K_XL with the model's own MTP head (DFlash2 sidecar kept on disk, one env change away), 2x Radeon AI PRO R9700 in ONE layer-split process (35:30 — skewed toward the x16-slot card; the other sits behind a Gen4 x1 chipset path), 393216 ctx over 2 slots of 196608, batch 6144x512, vision (BF16 mmproj)|7770|
 | Dankclaw | `frank-large` | halogen-flash-server 0.5.8 (rootless Quadlet) | peonist-ai Qwen3.8-Flash-Next w4b `.hgn` on the gfx1151 iGPU (Strix Halo LPDDR), 200192 ctx per conversation over one 400384-position KV pool / 2 slots, text only | 7770 |
-| Dankclaw | `frank-small` | mainline llama.cpp master 37b53fd (root systemd unit) | HauhauCS Gemma4-12B-QAT-Uncensored-Balanced Q4_K_M (BF16 mmproj + MTP assistant sidecar, `draft-mtp,ngram-mod`) on the RTX 3090, 1048576 pool / 4 slots of 262,144, q8_0 KV, the fleet's vision endpoint | 7771 |
+| Dankclaw | `frank-small` | vLLM `gemma-x86_64-cu129` dev build + audio extra (rootless Quadlet) | google/gemma-4-12B-it-qat-w4a16-ct (compressed-tensors w4a16, Marlin) + Google's bf16 MTP assistant on the RTX 3090, 262144 window / 289,647-token bf16 KV pool / 2 full-context sessions, native text+image+audio — the fleet's multimodal endpoint | 7771 |
 
 Retired endpoints (`frank-npu`, and every prior runtime) are in
 the [runbook index](#runbook-index). The full swap history lives in
@@ -68,8 +68,8 @@ All edits flow through git. Never edit files on a remote machine directly.
 The planner maps changed paths to services; the remote runner restarts only
 the selected service and records its revision outside the checkout.
 Documentation-only changes are a no-op. LLM services are selected only by
-their own files — frank-large by `dankclaw/frank-large/quadlet/`, frank-small
-and frank-medium by their unit/env/serve trio in `scripts/` — so unrelated
+their own files — frank-large and frank-small by their `dankclaw/`
+quadlet/Dockerfile directories, frank-medium by its unit/env/serve trio in `scripts/` — so unrelated
 container changes cannot interrupt inference. Set `FRANK_SUDO_PW` for headless
 runs on a host without passwordless sudo; the value never enters the repo.
 
@@ -232,8 +232,10 @@ merely wedged kernel usually still answers ARP.
      `~/.config/containers/systemd/frank-large.container` aside and
      `systemctl --user daemon-reload` — the quadlet generator re-creates that
      unit from the file on every reload, so the source is the lever, not `mask`.
-   - Dankclaw `frank-small` (root unit, llama.cpp on the 3090):
-     `sudo systemctl stop frank-small && sudo systemctl mask frank-small`
+   - Dankclaw `frank-small` (rootless Quadlet since 2026-09-19, vLLM on the 3090):
+     `systemctl --user stop frank-small`, then move its
+     `~/.config/containers/systemd/frank-small.container` aside and
+     `systemctl --user daemon-reload` (same quadlet-source lever as frank-large).
    - Dankserver `frank-medium` (system unit):
      `sudo systemctl stop frank-medium && sudo systemctl mask frank-medium`
 2. Bench.
@@ -263,10 +265,10 @@ When renaming a service, retiring an endpoint, or moving a model: update the
 provider block, model `id`, `contextWindow`, `maxTokens`, `input` in
 `models.yml`, then fix every `modelRoles` entry that named the old endpoint —
 a role pointing at a provider the file does not define fails at call time. As
-of 2026-09-16 the image path is `frank-small` (`input: [text, image]`), and
-`frank-large` is text-only because its halogen deployment loads no vision
-tower. There is **no audio** input anywhere in the fleet: that capability left
-with the FLM NPU endpoint on 2026-09-11.
+of 2026-09-19 `frank-small` is the fleet's multimodal endpoint
+(`input: [text, image, audio]`) — vLLM's native Gemma4 vision AND audio
+towers, both verified live. `frank-large` is text-only because its halogen
+deployment loads no vision tower.
 
 ### frank-large — halogen-flash-server (Dankclaw, ACTIVE)
 
@@ -301,31 +303,37 @@ that as "tight and fragmented", not "out of memory".
 Runbook: `serverAppConfigs-docs/LLM/halogen-flash-server.md`.
 Rollback: [[frank-large-ik-uncensored]].
 
-### frank-small — llama.cpp on the RTX 3090 (Dankclaw, ACTIVE)
+### frank-small — vLLM on the RTX 3090 (Dankclaw, ACTIVE)
 
-Mainline llama.cpp master `37b53fd` (CUDA build with
-`-DGGML_CUDA_FA_ALL_QUANTS=ON`) as a **root systemd unit** (repo
-`scripts/frank-small.service`, `relink_unit`ed into `/etc/systemd/system/`),
-serving `HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced` at Q4_K_M.
-The MTP head is a SEPARATE assistant file (`mtp-gemma-4-12B-it.gguf`, 4
-nextn layers) loaded via `--model-draft`; the draftless **ngram-mod**
-matcher chains behind it in the same `--spec-type` value. BF16 mmproj,
-port 7771, q8_0 KV, `CTX_SIZE=1048576` / `PARALLEL=4`
-(four FULL 262,144-token slots — the measured card ceiling), batch
-**8192/1024**, greedy default. Deployed flags are in
-`scripts/frank-small.env`; the serve script refuses to start if the
-weights, the projector, the sidecar or the binary are missing.
+vLLM `vllm/vllm-openai` dev build `gemma-x86_64-cu129` (digest-pinned, audio
+extra pip-installed into `localhost/vllm/vllm-openai:frank-small` — see
+`dankclaw/frank-small/Dockerfile`) as a **rootless Quadlet**
+(`dankclaw/frank-small/quadlet/frank-small.container`), serving
+`google/gemma-4-12B-it-qat-w4a16-ct` (compressed-tensors w4a16, int4 Marlin
+weights, 10.26 GiB) with Google's **bf16** MTP assistant
+(`google/gemma-4-12B-it-assistant`, 845 MB). Port 7771, 262,144 window,
+bf16 KV pool of 289,647 tokens, **2 concurrent full-context sessions**
+(the 3rd queues), CUDA graphs on, `ENFORCE_EAGER=0`.
 
-Verified at deploy (2026-09-17): `/v1/models` reports `frank-small`; a
-chat completion returns content plus `reasoning_content`; a tool call
-returns `tool_calls`; an image request is answered from the projector;
-an `input_audio` WAV transcribes verbatim. Post-tuning live numbers at
-max length: pp@254k ~965 t/s, tg@253k 226–302 t/s with ~94% draft
-acceptance; idle 23,300 MiB of 24,576. The throughput sweep (and why
-ubatch 2048 OOMs the draft's pp buffer, and why draft depth 4 + poll
-100 is WORSE at long ctx) is tabled in the runbook.
-Runbook: `serverAppConfigs-docs/LLM/frank-small-gemma4-12b.md`.
-Rollback: [[frank-small-qwen38-gsq-rco]].
+The w4a16-ct assistant CANNOT draft in vLLM (the drafter path skips the
+Marlin kernel — packed int4 misread, acceptance 1.00); the bf16 assistant
+measures acceptance 2.80–3.56. fp8 KV is hardware-dead on sm_86 (Ampere
+has no fp8 tensor cores), so bf16 is the only option.
+
+Dankclaw has **no nvidia-container-toolkit**: the unit wires CUDA by hand
+(`Device=` for the four nvidia nodes + host `libcuda`/`libnvidia-ml`
+mounted read-only into two library paths). Host driver is
+`nvidia-driver-610` 610.57.04 on Ubuntu 26.04; `sm_86` is the correct
+compute capability — no arch override.
+
+Verified at deploy (2026-09-19): `/v1/models` reports `frank-small`; chat
+returns content plus `reasoning` (vLLM's gemma4 parser field — the harness
+maps it via `compat.reasoningContentField`); a tool call returns
+`tool_calls`; an image is described; a 440 Hz WAV is described (native
+audio encoder). Measured: pp@67k 1,293 t/s, pp@213k 608 t/s,
+tg@213k ~13.6 t/s (bandwidth-bound), tg@85k ~17.6 t/s.
+Runbook: `serverAppConfigs-docs/LLM/frank-small-vllm-gemma4.md`.
+Rollback: [[frank-small-gemma4-12b]] (llama.cpp, weights still on host).
 
 ### frank-medium — llama.cpp layer split, MTP drafter (Dankserver, ACTIVE)
 
@@ -707,7 +715,7 @@ Active:
 | Service | Runbook |
 |---------|---------|
 | frank-large (halogen-flash-server, Dankclaw) | `serverAppConfigs-docs/LLM/halogen-flash-server.md` |
-| frank-small (llama.cpp Gemma4-12B QAT, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-gemma4-12b.md` |
+| frank-small (vLLM Gemma4-12B w4a16, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-vllm-gemma4.md` |
 | frank-medium (llama.cpp + MTP, Dankserver) | `serverAppConfigs-docs/LLM/frank-medium-llamacpp-dflash2.md` |
 | Dankclaw kernel posture (`amd_iommu=off`) | `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md` |
 | Deployment flow + incidents | `serverAppConfigs-docs/LLM/deployment.md` |
@@ -719,6 +727,7 @@ Retired (rollback targets and history):
 | kingjones STRIX Qwen3.8-Flash-Next ROCmFP4 | Dankclaw | 2026-08-30 → 09-11 | `kingjones-strix-rocmfp4.md` |
 | ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M (`frank-large`) | Dankclaw | 2026-09-15 → 09-16 | `frank-large-ik-uncensored.md` |
 | ISTA-DASLab Qwen3.8-27B-GSQ-RCO IQ3_S (`frank-small`) | Dankclaw | 2026-09-16 → 09-17 | `frank-small-qwen38-gsq-rco.md` |
+| llama.cpp Gemma4-12B QAT Q4_K_M (`frank-small`) | Dankclaw | 2026-09-17 → 09-19 | `frank-small-gemma4-12b.md` |
 | agentionai ROCmFP4-FAST imatrix | Dankclaw | 2026-08-29 → 08-30 | `agentionai-fast-imatrix.md` |
 | eemin Qwen3.8-27B ROCmI4 W4A4 MTP | Dankclaw | 2026-08-18 → 08-25 | `eemin-rocmi4-mtp.md` |
 | Kairic Edge IU4 | Dankclaw | 2026-08-22 (same-day revert) | `kairic-edge.md` |
diff --git a/dankclaw/frank-small/Dockerfile b/dankclaw/frank-small/Dockerfile
new file mode 100644
index 0000000..6268bd6
--- /dev/null
+++ b/dankclaw/frank-small/Dockerfile
@@ -0,0 +1,22 @@
+# frank-small runtime image: the digest-pinned vLLM gemma-x86_64-cu129 base
+# (vLLM 0.22.1rc1.dev357+g74b5964f0 — the image that loads
+# gemma-4-12B-it-qat-w4a16-ct, runs the Gemma4MTPModel drafter and carries
+# the gemma4 reasoning/tool-call parsers) plus the vllm[audio] extra.
+#
+# The base image ships WITHOUT the audio extras, so an input_audio content
+# part 500s with "Please install vllm[audio] for audio support" (measured
+# 2026-09-19). The extra is just four PyPI packages (av, scipy, soundfile,
+# mistral_common[audio]); installing the extras directly — not
+# `pip install vllm[audio]` — keeps the pinned dev build in place: a bare
+# `vllm[audio]` would make pip reach for the PyPI release and replace the
+# 0.22.1rc1.dev build that knows gemma4.
+#
+# Built by scripts/deploy-remote.sh on dankclaw (rootless podman, network on
+# for pip): the base is pulled by digest and re-tagged to the FROM ref below
+# first, then `podman build` produces the :frank-small tag the quadlet runs.
+FROM localhost/vllm/vllm-openai:gemma4-unified
+
+# The vllm[audio] extra as raw packages (header explains why not
+# `pip install vllm[audio]`): audio input needs av/scipy/soundfile plus
+# the mistral_common audio protocol pieces.
+RUN pip install --no-cache-dir av scipy soundfile "mistral_common[audio]"
diff --git a/dankclaw/frank-small/quadlet/frank-small.container b/dankclaw/frank-small/quadlet/frank-small.container
new file mode 100644
index 0000000..770decc
--- /dev/null
+++ b/dankclaw/frank-small/quadlet/frank-small.container
@@ -0,0 +1,100 @@
+# Quadlet unit: frank-small (rootless, boot-persistent).
+#
+# Install path on dankclaw: ~/.config/containers/systemd/frank-small.container
+# Unit name: frank-small.service (container name: frank-small)
+#
+# The small inference service. vLLM (since 2026-09-18) serving
+# google/gemma-4-12B-it-qat-w4a16-ct (compressed-tensors w4a16) with the
+# google bf16 MTP assistant for speculative decoding, on the RTX
+# 3090. It replaced the mainline-llama.cpp ROOT unit (the old
+# scripts/frank-small.service is retired into scripts/.AGENTTRASH/).
+#
+# SHAPE. The quadlet replaces the image's `vllm serve` entrypoint with
+# /scripts/serve-frank-small.sh (mounted read-only out of the repo checkout)
+# so the flag set stays in git. The model and drafter directories are bound
+# read-only: the payloads are fetched and sha256-verified by
+# scripts/download-frank-small-vllm.sh before first start, and the deploy
+# handler refuses to start the unit when either is absent.
+#
+# CUDA WITHOUT the nvidia-container-toolkit. This host has never run a CUDA
+# container (the 3090 served frank-small as a native binary, the iGPU runs
+# ROCm through /dev/kfd), so there is no nvidia hook to lean on. The recipe
+# that works (measured 2026-09-18, torch sees the 3090 at 25.3 GB):
+#   - the four /dev/nvidia* nodes via AddDevice (they are 0666 on this host,
+#     so the rootless user namespace can open them);
+#   - the HOST driver's libcuda.so.1 and libnvidia-ml.so.1 mounted read-only
+#     — the image carries its own CUDA 12.9 runtime, but vLLM's platform
+#     probe needs the driver's NVML stub, and without it `vllm serve` dies at
+#     parser construction with "Failed to infer device type";
+#   - NVIDIA_VISIBLE_DEVICES=all.
+# memlock must be unlimited: CUDA pins its staging buffers.
+#
+# SIZING. The tunables (full 262144 window, 0.95 of a dedicated 24 GiB card,
+# bf16 KV, 16-seq batch ceiling, 16k prefill chunk, 4-token MTP draft) live
+# in scripts/frank-small.env. The boot log's "Maximum concurrency for N
+# tokens per request" line is the naive pool ratio for a hybrid SWA model
+# and undercounts; verify the session count behaviourally on restart.
+#
+# IMAGE. The unit runs the localhost/-aliased tag: this host's podman quadlet
+# path cannot resolve registry-prefixed refs from local storage at create
+# time. The tag is a LOCAL BUILD, not a pull: deploy-remote.sh pulls the
+# digest-pinned docker.io base (the gemma-x86_64-cu129 build, vLLM
+# 0.22.1rc1.dev357+g74b5964f0 — the image that boots this checkpoint) and
+# re-tags it, then builds dankclaw/frank-small/Dockerfile on top, which
+# installs the vllm[audio] extra (av, scipy, soundfile,
+# mistral_common[audio]) so the model's native audio path works. Pull=never
+# keeps boots off the registry.
+[Unit]
+Description=frank-small — vLLM gemma4_unified w4a16 + MTP on RTX 3090
+After=network-online.target
+
+[Container]
+ContainerName=frank-small
+Image=localhost/vllm/vllm-openai:frank-small
+# Published port stays 7771: Hermes, the harness and the homepage probe all
+# point here. 8000 (vLLM's in-container port) is never reachable directly.
+PublishPort=7771:8000
+# CUDA device nodes (0666 on this host — rootless can open them).
+AddDevice=/dev/nvidia0
+AddDevice=/dev/nvidiactl
+AddDevice=/dev/nvidia-uvm
+AddDevice=/dev/nvidia-uvm-tools
+# Host driver stubs the image's CUDA runtime and vLLM's NVML probe need.
+# The image's LD_LIBRARY_PATH leads with /usr/local/nvidia/lib64 — the
+# nvidia-container-toolkit's conventional mount point, which this host does
+# not have — so the driver libs go there; the /usr/lib mounts cover torch
+# Inductor's own lookup.
+Volume=/usr/lib/x86_64-linux-gnu/libcuda.so.1:/usr/lib/x86_64-linux-gnu/libcuda.so.1:ro
+Volume=/usr/lib/x86_64-linux-gnu/libcuda.so:/usr/lib/x86_64-linux-gnu/libcuda.so:ro
+Volume=/usr/lib/x86_64-linux-gnu/libnvidia-ml.so.1:/usr/lib/x86_64-linux-gnu/libnvidia-ml.so.1:ro
+Volume=/usr/lib/x86_64-linux-gnu/libcuda.so.1:/usr/local/nvidia/lib64/libcuda.so.1:ro
+Volume=/usr/lib/x86_64-linux-gnu/libcuda.so:/usr/local/nvidia/lib64/libcuda.so:ro
+Volume=/usr/lib/x86_64-linux-gnu/libnvidia-ml.so.1:/usr/local/nvidia/lib64/libnvidia-ml.so.1:ro
+Environment=NVIDIA_VISIBLE_DEVICES=all
+# Payloads, read-only: fetched and sha256-verified by
+# scripts/download-frank-small-vllm.sh before first start.
+Volume=/home/dank/models/gemma4-12b-qat-w4a16-ct:/models/main:ro
+Volume=/home/dank/models/gemma4-12b-assistant-bf16:/models/assistant:ro
+# Serve script and env, read-only out of the repo checkout.
+Volume=/home/dank/serverAppConfigs/scripts:/scripts:ro
+ContainerEntrypoint=/scripts/serve-frank-small.sh
+Environment=FRANK_SMALL_ENV_FILE=/scripts/frank-small.env
+Ulimit=memlock=-1:-1
+# /health answers 200 once the engine is up; vLLM 503s it while the model is
+# still loading, so a green check means ready-to-serve, not process-alive.
+# curl ships in the image.
+HealthCmd=curl -sf http://127.0.0.1:8000/health
+HealthInterval=30s
+HealthTimeout=10s
+HealthRetries=3
+HealthStartPeriod=600s
+Pull=never
+
+[Service]
+# First start reads ~10 GiB of weights and compiles the CUDA graphs.
+TimeoutStartSec=900
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=default.target
diff --git a/scripts/deploy-plan.py b/scripts/deploy-plan.py
index 2fa5aea..accac4f 100755
--- a/scripts/deploy-plan.py
+++ b/scripts/deploy-plan.py
@@ -319,6 +319,12 @@ def services_for_path(path: str, target: str) -> set[str]:
             # its unit and fleet settings live in one .container file.
             _add(services, "frank-large")
             return services
+        if len(parts) >= 2 and parts[1] == "frank-small":
+            # The service is a rootless Quadlet container since 2026-09-18
+            # (vLLM); its unit lives in one .container file. The old root
+            # unit's trio is in scripts/ and maps there.
+            _add(services, "frank-small")
+            return services
         if len(parts) >= 2 and parts[1] == "observability":
             # The five observability containers became Quadlet units on
             # 2026-09-11. A unit change selects exactly its own service;
@@ -402,11 +408,13 @@ def services_for_path(path: str, target: str) -> set[str]:
             # change to it redeploying alertmanager is the only path that
             # reaches it on the host.
             _add(services, "alertmanager")
-        if name in {"frank-small.env", "frank-small.service", "serve-frank-small.sh"}:
-            # llama.cpp frank-small (2026-09-16) keeps its unit, env and serve
-            # files here; each one selects frank-small only. The ik_llama.cpp
-            # trio that lived here for two days is in scripts/.AGENTTRASH/,
-            # which is archive material and plans nothing.
+        if name in {"frank-small.env", "serve-frank-small.sh",
+                    "download-frank-small-vllm.sh"}:
+            # vLLM frank-small (2026-09-18) keeps its env, entrypoint and
+            # fetch script here; each one selects frank-small only. The
+            # unit is the quadlet under dankclaw/frank-small/, and the old
+            # root unit file is in scripts/.AGENTTRASH/, which is archive
+            # material and plans nothing.
             _add(services, "frank-small")
         if name in {"frank-medium.env", "frank-medium.service", "serve-frank-medium.sh"}:
             # llama.cpp frank-medium (2026-09-16) keeps its unit, env and serve
diff --git a/scripts/deploy-remote.sh b/scripts/deploy-remote.sh
index c1216ac..1cae4f5 100755
--- a/scripts/deploy-remote.sh
+++ b/scripts/deploy-remote.sh
@@ -1139,28 +1139,90 @@ wait_for_llm_large_ready() {
     return 0
 }
 
-# deploy_llm_small — frank-small is mainline llama.cpp on the RTX 3090, as a
-# ROOT unit: the runtime is a native CUDA binary, so there is no container
-# image to install and no generated unit to avoid. relink_unit points
-# /etc/systemd/system/frank-small.service at the repo file and boot persistence
-# is that unit's [Install] section.
+# deploy_llm_small — frank-small is a rootless Quadlet running vLLM on the
+# RTX 3090 since 2026-09-18: the runtime is the digest-pinned
+# vllm/vllm-openai gemma4-unified image, and the unit is generated from
+# dankclaw/frank-small/quadlet/. It replaces the mainline-llama.cpp
+# deployment, which ran as a ROOT unit.
 #
-# It is a SEPARATE endpoint on port 7771; frank-large keeps 7770. The 3090 is
-# not shared: frank-large's halogen engine runs on the gfx1151 iGPU.
-LLM_SMALL_MODEL="${LLM_SMALL_MODEL:-/home/dank/models/Gemma4-12B-QAT/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf}"
+# TWO MANAGERS, ONE UNIT NAME. The llama.cpp incarnation ran as a ROOT unit
+# whose file is a symlink into this checkout; the vLLM unit is a USER
+# (quadlet) unit. Both must never exist at once — they would race for port
+# 7771 — so the root unit is retired first: stop, disable, move the /etc
+# symlink into the home trash (never `rm`), reload the root manager. This
+# host's `systemctl disable` has been observed to delete the unit file
+# itself (2026-08-26 incident), so the move tolerates a file that is
+# already gone.
+#
+# The payloads are fetched and sha256-verified by
+# scripts/download-frank-small-vllm.sh before first start; the handler
+# refuses to launch a unit that cannot load its model or its drafter.
+LLM_SMALL_MODEL="${LLM_SMALL_MODEL:-/home/dank/models/gemma4-12b-qat-w4a16-ct/model.safetensors}"
+LLM_SMALL_DRAFT="${LLM_SMALL_DRAFT:-/home/dank/models/gemma4-12b-assistant-bf16/model.safetensors}"
+# Base image: the gemma-x86_64-cu129 build (vLLM 0.22.1rc1.dev357+
+# g74b5964f0) — the image that boots this checkpoint. The June 3
+# gemma4-unified build predates it and fails at weight load (missing
+# vision_embedder.patch_dense); the Sep 15 cu129-nightly fails at import
+# (torchvision ABI). The unit runs a LOCAL BUILD on top of this base —
+# dankclaw/frank-small/Dockerfile installs the vllm[audio] extra, which
+# the base ships without.
+VLLM_SMALL_BASE_IMAGE="docker.io/vllm/vllm-openai@sha256:e24d3d8e367ebc2a6ccfc8cf3cecee858a30a6c66b5b1642d85363cd745e001e"
+VLLM_SMALL_BASE_ALIAS="localhost/vllm/vllm-openai:gemma4-unified"
+VLLM_SMALL_IMAGE="localhost/vllm/vllm-openai:frank-small"
+
+retire_root_llm_small() {
+    local trash="$HOME/.AGENTTRASH/20260918-vllm-cutover/host-units"
+    run_privileged systemctl stop frank-small.service 2>/dev/null || true
+    run_privileged systemctl disable frank-small.service 2>/dev/null || true
+    if [[ -e /etc/systemd/system/frank-small.service || -L /etc/systemd/system/frank-small.service ]]; then
+        mkdir -p "$trash"
+        run_privileged mv -- /etc/systemd/system/frank-small.service \
+            "$trash/frank-small.service"
+        echo "retired root unit frank-small.service -> $trash"
+    else
+        # This host's `systemctl disable` is allowed to delete the unit file
+        # outright (2026-08-26 incident), so there is often nothing left to
+        # move. Say so: previously no message meant no evidence either way.
+        echo "root unit frank-small.service was already removed by disable"
+    fi
+    run_privileged systemctl daemon-reload
+}
 
 deploy_llm_small() {
     if [[ ! -f "$LLM_SMALL_MODEL" ]]; then
         echo "ERROR: model absent at $LLM_SMALL_MODEL" >&2
-        echo "frank-small: fetch HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M, the mmproj and the MTP sidecar) first;" >&2
+        echo "frank-small: run scripts/download-frank-small-vllm.sh first (main model + MTP assistant, sha256-verified);" >&2
         echo "frank-small: refusing to start a unit that cannot load." >&2
         return 1
     fi
-    relink_unit frank-small
-    run_privileged systemctl daemon-reload
-    run_privileged systemctl enable frank-small.service
-    run_privileged systemctl restart frank-small.service
-    wait_for_health frank-small http://127.0.0.1:7771/health 900
+    if [[ ! -f "$LLM_SMALL_DRAFT" ]]; then
+        echo "ERROR: MTP assistant absent at $LLM_SMALL_DRAFT" >&2
+        echo "frank-small: run scripts/download-frank-small-vllm.sh first;" >&2
+        echo "frank-small: refusing to start a unit that cannot draft." >&2
+        return 1
+    fi
+    retire_root_llm_small
+    # The predecessor can also be THIS quadlet -- a redeploy of a running
+    # frank-small -- so stop the user unit before waiting on the port. On a
+    # first cutover it is not running and this is a no-op.
+    systemctl --user stop frank-small.service 2>/dev/null || true
+    # Pull the base by digest, re-tag it to the FROM ref the Dockerfile
+    # expects, then build the derived image the quadlet runs: the quadlet
+    # path cannot resolve registry-prefixed refs from local storage at
+    # create time (same workaround as halogen), and Pull=never keeps boots
+    # off the registry. The build needs network for pip (the vllm[audio]
+    # extra); podman build has it on by default.
+    podman pull "$VLLM_SMALL_BASE_IMAGE"
+    podman tag "$VLLM_SMALL_BASE_IMAGE" "$VLLM_SMALL_BASE_ALIAS"
+    podman build --pull=never -t "$VLLM_SMALL_IMAGE" \
+        -f dankclaw/frank-small/Dockerfile dankclaw/frank-small
+    # Nothing may start until the predecessor has released the port.
+    wait_port_free 7771 || return 1
+    install_quadlet frank-small dankclaw/frank-small/quadlet frank-small
+    # No enable: generated units cannot be enabled on this host (v1 quadlet
+    # generator); boot persistence comes from [Install] in the unit file.
+    systemctl --user restart frank-small.service
+    wait_for_health frank-small http://127.0.0.1:7771/health 1200
 }
 
 # deploy_llm_medium — frank-medium is mainline llama.cpp on the two R9700s as a
diff --git a/scripts/download-frank-small-vllm.sh b/scripts/download-frank-small-vllm.sh
new file mode 100755
index 0000000..4d811b0
--- /dev/null
+++ b/scripts/download-frank-small-vllm.sh
@@ -0,0 +1,80 @@
+#!/usr/bin/env bash
+# Fetch the frank-small vLLM payloads on dankclaw (RTX 3090, since 2026-09-18):
+#
+#   google/gemma-4-12B-it-qat-w4a16-ct
+#       compressed-tensors w4a16 (int4, group 32) QAT checkpoint — the model
+#       vLLM's gemma4_unified implementation loads natively. One 9.56 GiB
+#       safetensors plus tokenizer/config.
+#
+#   google/gemma-4-12B-it-assistant
+#       the MTP draft/assistant (gemma4_unified_assistant, 4 layers) in
+#       bf16 — Google's original. 806 MiB. The w4a16-ct re-quant
+#       (kunhunjon) that was used first drafts at acceptance 1.00: vLLM's
+#       MTP drafter path does not apply the Marlin w4a16 kernel to the
+#       assistant's linears (no "Using MarlinLinearKernel" after the
+#       drafter load), so its packed int4 weights are misread. The bf16
+#       assistant accepts at 2.80 (measured 2026-09-19).
+#
+# Both repos are public and ungated; no token is needed. Every fetch is -f
+# (an HTTP error is a failure, not a 153-byte "artifact"), resumable, and the
+# two LFS payloads are sha256-verified against the Hub's declared oid — the
+# discipline from scripts/download-frank-medium-gguf.sh.
+#
+# The serve script refuses to start when either payload is absent, so a
+# half-finished run of this script reads as a missing file, not a runtime
+# fault.
+set -euo pipefail
+
+MODELS_DIR="${MODELS_DIR:-/home/dank/models}"
+LOG_DIR="$MODELS_DIR/logs"
+mkdir -p "$LOG_DIR"
+LOG="$LOG_DIR/$(basename "$0" .sh).log"
+
+log() { echo "$(date -Is) $*" | tee -a "$LOG"; }
+
+# fetch <repo> <dir> <file> [sha256] [size]
+fetch() {
+    local repo="$1" dir="$2" file="$3" sha="${4:-}" size="${5:-}"
+    mkdir -p "$dir"
+    if [[ -n "$size" && -f "$dir/$file" ]] && [[ "$(stat -c%s "$dir/$file")" == "$size" ]]; then
+        log "skip $dir/$file (size $size matches)"
+    else
+        log "fetch $repo/$file"
+        curl -fsSL -C - "https://huggingface.co/$repo/resolve/main/$file" -o "$dir/$file"
+        log "fetched $dir/$file ($(stat -c%s "$dir/$file") bytes)"
+    fi
+    if [[ -n "$sha" ]]; then
+        local actual
+        actual="$(sha256sum "$dir/$file" | cut -d' ' -f1)"
+        if [[ "$actual" != "$sha" ]]; then
+            log "SHA256 MISMATCH $dir/$file: $actual != $sha"
+            return 1
+        fi
+        log "sha256 ok $dir/$file"
+    fi
+}
+
+MAIN_REPO=google/gemma-4-12B-it-qat-w4a16-ct
+ASSISTANT_REPO=google/gemma-4-12B-it-assistant
+MAIN_DIR="$MODELS_DIR/gemma4-12b-qat-w4a16-ct"
+ASSISTANT_DIR="$MODELS_DIR/gemma4-12b-assistant-bf16"
+
+# Hub-declared LFS oids (sha256), 2026-09-18.
+fetch "$MAIN_REPO" "$MAIN_DIR" model.safetensors \
+    60b6e3989502969d8ae04185d72ecbbc7db63978d5af747a493d53895aa6bfa3 10264229896
+fetch "$MAIN_REPO" "$MAIN_DIR" tokenizer.json \
+    cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f 32169626
+for f in config.json generation_config.json chat_template.jinja \
+         processor_config.json tokenizer_config.json recipe.yaml; do
+    fetch "$MAIN_REPO" "$MAIN_DIR" "$f"
+done
+
+fetch "$ASSISTANT_REPO" "$ASSISTANT_DIR" model.safetensors \
+    3279c173daddd7186e79d652ad94022415736d3a1370625696c898429b06d6df 845719296
+fetch "$ASSISTANT_REPO" "$ASSISTANT_DIR" tokenizer.json \
+    c001d9ada50af662c94f5ab17ec7e09f6438d1bec8246c47fee6510693d8de35 32169884
+for f in config.json generation_config.json tokenizer_config.json; do
+    fetch "$ASSISTANT_REPO" "$ASSISTANT_DIR" "$f"
+done
+
+log "ALL FETCHED OK"
diff --git a/scripts/frank-small.env b/scripts/frank-small.env
index 42d8431..bbf71a0 100644
--- a/scripts/frank-small.env
+++ b/scripts/frank-small.env
@@ -1,112 +1,81 @@
-# Tunables for frank-small (HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-
-# Balanced, Q4_K_M, plus the BF16 vision projector and the separate MTP
-# sidecar) on mainline llama.cpp, Dankclaw's RTX 3090, since 2026-09-17.
+# Tunables for frank-small (since 2026-09-18): vLLM serving
+# google/gemma-4-12B-it-qat-w4a16-ct (compressed-tensors w4a16 — the format
+# Google publishes "for native, optimized inference with vLLM") with the
+# google bf16 MTP assistant, on Dankclaw's RTX 3090.
 #
-# Runtime: llama.cpp master 37b53fd, CUDA build for sm_86:
-#   cmake -B build-cuda -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=ON \
-#     -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=86 -DGGML_CUDA_FA_ALL_QUANTS=ON
-#   cmake --build build-cuda --target llama-server -j
-# GGML_CUDA_FA_ALL_QUANTS is ON: this service runs q8_0 KV with flash
-# attention, and without the flag quantized-KV prefill collapses ~12x on
-# CUDA (see the CUDA lesson in AGENTS.md).
+# Runtime: the vllm/vllm-openai gemma-x86_64-cu129 build (vLLM
+# 0.22.1rc1.dev357+g74b5964f0; base digest in scripts/deploy-remote.sh),
+# with the vllm[audio] extra installed on top (dankclaw/frank-small/
+# Dockerfile) so the model's native audio path works. That image carries
+# the native gemma4_unified implementation, the Gemma4MTPModel drafter,
+# the gemma4 reasoning and tool-call parsers, and CUDA 12.9 for the Ada
+# card. The older gemma4-unified build (June 3) predates this checkpoint
+# and fails at weight load; the cu129-nightly build (Sep 15) fails at
+# import (torchvision ABI); this one is the image that boots.
 #
-# Model: HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced at Q4_K_M
-# (6.87 GiB). Architecture (GGUF arch gemma4): 48 layers, MHA with 16 kv
-# heads x 512 head_dim, rope freq_base 1e6, final logit softcapping 30,
-# per-layer token embeddings (PLE) inside the file, and a sliding-window
-# attention pattern (attention.sliding_window = 1024) -- most layers cache
-# only a 1024-position window, which is why the KV pool is a fraction of
-# the full-ctx x all-layers number.
+# Model: 11.95B "unified" (encoder-free) — 48 layers of 5 sliding-window
+# (1024-token) + 1 full-attention, int4 group-32 weights with bf16
+# embeddings, vision and audio. The fleet's image path lives here: the model
+# ingests image (and audio) content natively, so no projector file exists
+# any more and nothing external has to load.
 #
-# MTP: the Multi-Token Prediction head ships as a SEPARATE file
-# (mtp-gemma-4-12B-it.gguf, arch gemma4-assistant, 4 nextn layers, 0.24
-# GiB). Unlike the Qwen3.8 -mtp build (head inside the main file), this one
-# is passed via --model-draft with --spec-type draft-mtp, so the draft
-# context loads the assistant model. The same --spec-type value chains the
-# draftless ngram-mod matcher, which attaches unconditionally; two
-# context-backed drafters cannot share one process, so draft-mtp,ngram-mod
-# is the only legal shape that carries both.
+# MTP: the draft model is a SEPARATE 4-layer assistant checkpoint in the
+# same int4 w4a16 compressed-tensors format — the card's compatibility rule
+# is that a QAT target must draft with a QAT drafter at the same precision.
+# It is passed in --speculative-config with method "mtp", vLLM's Gemma 4
+# MTP path, not a generic draft model.
 #
-# SIZING (RTX 3090, 24576 MiB): CTX_SIZE = PARALLEL x 262144 -- four
-# FULL-window slots, measured to fit: the 4-slot boot idles at 22,346
-# MiB and each extra full-context slot costs 3,450 MiB (measured 1-slot
-# 11,996 -> 4-slot 22,346). A fifth slot projects to ~25.8 GiB, past the
-# card, and the KV pool allocates upfront -- so 4 is the max. Explicit
-# CTX_SIZE bypasses --fit on purpose: --fit maximises the TOTAL pool,
-# which would shrink each slot below the full 262144 window once
-# parallel > 1.
+# SIZING (RTX 3090, 24576 MiB): the goal is the model's FULL 262144 window
+# for as many concurrent sessions as the card holds.
+#   MAX_MODEL_LEN=262144      the model's max_position_embeddings
+#   GPU_MEM_UTIL=0.95         the card is dedicated to this service
+#   KV_CACHE_DTYPE=auto       bf16 KV. fp8_e4m3 would halve the KV charge
+#                             (289,756 -> 623,666-token pool, one -> two
+#                             full-context sessions), but the 3090 is
+#                             sm_86 (Ampere) and has no native fp8: the
+#                             TRITON_ATTN backend Gemma4 forces emits
+#                             cvt.e4m3x2 instructions that exist only from
+#                             sm_89 (Ada), so fp8 KV cannot boot on this
+#                             card (measured 2026-09-19; the "sm_89
+#                             patch" experiment is in .AGENTTRASH).
+#   MAX_NUM_SEQS=16           the batch ceiling; the KV pool, not this,
+#                             caps full-context concurrency
+#   MAX_NUM_BATCHED_TOKENS=16384  the prefill chunk; larger chunks prefill
+#                             faster but grow the activation arena that
+#                             competes with the KV pool for the card
+# The boot log prints the KV pool size and "Maximum concurrency for N tokens
+# per request" — for a hybrid SWA model that line is the NAIVE ratio (pool /
+# max_model_len) and undercounts: the 42 sliding-window layers only retain a
+# 1024-token window per request, so the true full-context session count is
+# higher. Verify it behaviourally (concurrent long requests) on every
+# restart, not from these comments.
 #
-# Vision + audio: --mmproj loads the BF16 projector (11 tensors, 52M
-# params; it carries an audio encoder too). The fleet's image path lives
-# here, which is why halogen no longer sets HALOGEN_VISION_TOWER. Audio
-# WORKS: input_audio content parts transcribe verbatim (verified
-# 2026-09-17 with a 16k mono WAV).
+# Sampling: greedy by default (fleet contract) via
+# --override-generation-config; a client that sends its own temperature gets
+# its own, and the harness applies per-model overrides from models.yml.
 #
-# Sampling: greedy by default (the fleet contract); a client that sends a
-# temperature gets its own, and the harness applies per-model overrides
-# from models.yml.
-#
-# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (HIP
-# reads those bare vars on the ROCm hosts -- see the 2026-08-13 incident in
+# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (the
+# ROCm hosts read those bare vars — see the 2026-08-13 incident in
 # AGENTS.md). This box is CUDA, but the rule keeps env files portable.
 
-# llama.cpp runtime binary: mainline master 37b53fd, CUDA sm_86,
-# FA_ALL_QUANTS=ON.
-LLAMA_BIN=/home/dank/GitPackages/llama.cpp-mainline/build-cuda/bin/llama-server
+# Container paths, bind-mounted by the quadlet. The host paths are declared
+# in the quadlet and the deploy handler, not here: this file is read inside
+# the container.
+MODEL_DIR=/models/main
+DRAFT_DIR=/models/assistant
 
-# Model package. The MTP sidecar file is required for speculative decoding.
-MODEL_DIR=/home/dank/models/Gemma4-12B-QAT
-MODEL_FILE=Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf
-MMPROJ_PATH=/home/dank/models/Gemma4-12B-QAT/mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf
-DRAFT_FILE=mtp-gemma-4-12B-it.gguf
-
-# Fleet identity and network. 7771 is this service's own endpoint on
-# Dankclaw; 7770 stays frank-large's. The alias is the id at /v1/models and
-# what clients ask for -- the harness entry in models.yml names it.
+# Fleet identity. 8000 is the in-container port; the quadlet publishes it as
+# host 7771, the endpoint Hermes, the harness and the homepage probe have
+# always used. The alias is the id at /v1/models and what clients ask for.
 ALIAS=frank-small
 BIND_ADDR=0.0.0.0
-LISTEN_PORT=7771
+LISTEN_PORT=8000
 
-# Four FULL 262144-token contexts, one per slot (CTX_SIZE is the total
-# pool; --parallel divides it). See the SIZING note above for the fit
-# arithmetic; a fifth slot does not fit.
-CTX_SIZE=1048576
-PARALLEL=4
-CACHE_TYPE_K=q8_0
-CACHE_TYPE_V=q8_0
-
-# Batch geometry: 8192 logical / 1024 physical. Measured on this card at
-# max length (254k-token prefill / 253k-ctx decode, 4 slots, q8 KV):
-# ubatch 512 -> pp 915 t/s, tg@250k 90-204; ubatch 1024 -> pp 962,
-# tg 257-302. Larger ubatches (2048) OOM the MTP draft context's pp
-# compute buffer (~3.3 GiB against 2.2 GiB headroom) and must not be
-# tried. Idle VRAM is 23,300 MiB at this geometry.
-BATCH_SIZE=8192
-UBATCH_SIZE=1024
-
-# CPU threads: this service runs entirely on the GPU (NGL=999), so threads
-# cover tokenization, sampling and the HTTP layer only. Deliberately modest
-# -- this host's CPU is shared with halogen's engine, which is CPU-hungry.
-NUM_THREADS=8
-THREAD_BATCH=8
-
-# Every layer on the 3090, with flash attention (required for q8 KV).
-NGL=999
-FLASH_ATTN=on
-
-# Speculative decoding: the MTP sidecar (draft context) chained with the
-# draftless ngram-mod matcher. Draft depth and busy-wait level are made
-# explicit here (both were the implicit build defaults: 3 and 50).
-# Measured at 250k ctx: depth 4 + poll 100 DECODED WORSE (230-257 t/s)
-# than depth 3 + poll 50 (257-302 t/s) — the longer verification round
-# costs more attention re-read at long context than the extra accepted
-# token earns. Keep 3/50.
-SPEC_TYPE=draft-mtp,ngram-mod
-SPEC_DRAFT_N_MAX=3
-POLL_LEVEL=50
-
-# Greedy default (fleet contract); reasoning is extracted into
-# reasoning_content with an unlimited budget (the model decides).
-TEMPERATURE=0.0
-REASONING_FORMAT=deepseek
-REASONING_BUDGET=-1
+# Full window, dedicated card, bf16 KV (see above), roomy batch ceiling,
+# 16k prefill chunk, 4-token MTP draft (the assistant carries 4 layers).
+MAX_MODEL_LEN=262144
+GPU_MEM_UTIL=0.95
+KV_CACHE_DTYPE=auto
+MAX_NUM_SEQS=16
+MAX_NUM_BATCHED_TOKENS=16384
+SPEC_NUM_TOKENS=4
diff --git a/scripts/frank-small.service b/scripts/frank-small.service
deleted file mode 100644
index 14ddd9c..0000000
--- a/scripts/frank-small.service
+++ /dev/null
@@ -1,20 +0,0 @@
-[Unit]
-Description=llama.cpp Qwen3.8-27B GSQ-RCO IQ3_S MTP+vision (dankclaw, frank-small)
-After=network-online.target
-Wants=network-online.target
-
-[Service]
-Type=simple
-User=dank
-Group=dank
-# CUDA pins its staging buffers, so the process needs the memlock budget even
-# though the weights themselves are copied into VRAM. Parity with the halogen
-# quadlet's Ulimit=memlock=-1:-1 and the retired ik unit.
-LimitMEMLOCK=infinity
-Environment="FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-small.env"
-ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-small.sh
-Restart=on-failure
-RestartSec=10
-
-[Install]
-WantedBy=multi-user.target
diff --git a/scripts/serve-frank-small.sh b/scripts/serve-frank-small.sh
index 0a9aade..c5fcb03 100755
--- a/scripts/serve-frank-small.sh
+++ b/scripts/serve-frank-small.sh
@@ -1,43 +1,30 @@
 #!/usr/bin/env bash
-# Serve HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M) as
-# frank-small on Dankclaw's RTX 3090 via mainline llama.cpp.
+# Serve google/gemma-4-12B-it-qat-w4a16-ct as frank-small on Dankclaw's RTX
+# 3090 via vLLM (since 2026-09-18), with the google bf16 MTP assistant
+# for speculative decoding.
 #
-# Topology: the whole model lives in VRAM (-ngl 999) -- 6.87 GiB of Q4_K_M
-# weights plus the BF16 vision projector and q8_0 KV inside the card's
-# 24 GiB. The host CPU only tokenizes and samples here; this box's CPU
-# belongs to the halogen engine that serves frank-large.
+# This script is the CONTAINER ENTRYPOINT of the frank-small quadlet: the
+# vllm/vllm-openai image's own entrypoint is `vllm serve`, and the quadlet
+# replaces it with this file (mounted read-only out of the repo checkout) so
+# the flag set stays in git. The image pins the gemma4-unified vLLM build,
+# which is what loads gemma4_unified natively and runs the Gemma 4 MTP path.
 #
-# MTP: this model's Multi-Token Prediction head ships as a SEPARATE file
-# (mtp-gemma-4-12B-it.gguf, arch gemma4-assistant, 4 nextn layers). It is
-# passed via --model-draft with --spec-type draft-mtp: the draft context
-# loads the assistant model. The same --spec-type value chains the
-# draftless ngram-mod matcher, which attaches unconditionally; two
-# context-backed drafters cannot share one process, so this chain is the
-# only shape that carries both.
+# MTP: the drafter is a separate 4-layer assistant checkpoint in bf16
+# (Google's original gemma-4-12B-it-assistant). It goes in
+# --speculative-config as method "mtp" — vLLM's Gemma 4 MTP path, not a
+# generic draft model. The w4a16-ct re-quant of the assistant was tried
+# first and drafts at acceptance 1.00 (the drafter path does not apply the
+# Marlin kernel to its linears); the bf16 assistant accepts at 2.80.
 #
-# Context: CTX_SIZE is set explicitly to PARALLEL x 262144 so every slot
-# gets the model's FULL window; --fit (the CTX_SIZE-unset branch below)
-# maximises the TOTAL pool instead, which would divide a smaller window
-# across slots. The 4-slot layout is measured to fit the card (see the
-# SIZING note in frank-small.env); more slots would fail the KV allocation.
+# Sampling: greedy by default (fleet contract) via
+# --override-generation-config; clients that send their own temperature get
+# their own, and the harness overrides per model from models.yml.
 #
-# Vision + audio: --mmproj loads the BF16 projector, which also carries
-# an audio encoder — input_audio content parts transcribe verbatim
-# (verified 2026-09-17). The fleet's image path lives here, which is why
-# halogen no longer sets HALOGEN_VISION_TOWER.
-#
-# Sampling: greedy by default (the fleet contract). Clients that send their own
-# temperature get their own values, and the harness overrides per model from
-# models.yml. --jinja is pinned even though this build defaults it on: the
-# model's own template supplies reasoning_effort, preserve_thinking and the
-# tool-call grammar, and a future build that flips that default must not
-# silently take tools away.
-#
-# Tunables come from frank-small.env unless FRANK_SMALL_ENV_FILE overrides it.
+# Tunables come from frank-small.env (mounted beside this file by the
+# quadlet) unless FRANK_SMALL_ENV_FILE overrides the path.
 set -euo pipefail
 
-SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
-ENV_FILE="${FRANK_SMALL_ENV_FILE:-$SCRIPT_DIR/frank-small.env}"
+ENV_FILE="${FRANK_SMALL_ENV_FILE:-/scripts/frank-small.env}"
 if [[ -f "$ENV_FILE" ]]; then
     set -a
     # shellcheck disable=SC1090
@@ -46,93 +33,51 @@ if [[ -f "$ENV_FILE" ]]; then
 fi
 
 # --- defaults (used when the env file does not set them) -------------------
-: "${LLAMA_BIN:=/home/dank/GitPackages/llama.cpp-mainline/build-cuda/bin/llama-server}"
-: "${MODEL_DIR:=/home/dank/models/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp}"
-: "${MODEL_FILE:=Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf}"
-: "${MMPROJ_PATH:=$MODEL_DIR/mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf}"
-: "${DRAFT_FILE:=}"
+: "${MODEL_DIR:=/models/main}"
+: "${DRAFT_DIR:=/models/assistant}"
 : "${ALIAS:=frank-small}"
 : "${BIND_ADDR:=0.0.0.0}"
-: "${LISTEN_PORT:=7771}"
-: "${CTX_SIZE:=}"
-: "${PARALLEL:=1}"
-: "${CACHE_TYPE_K:=f16}"
-: "${CACHE_TYPE_V:=f16}"
-: "${BATCH_SIZE:=2048}"
-: "${UBATCH_SIZE:=512}"
-# Decode-shape knobs: the MTP drafter's per-round proposal length (build
-# default 3; the Gemma4 sidecar carries 4 nextn layers) and the engine's
-# busy-wait level (build default 50).
-: "${SPEC_DRAFT_N_MAX:=3}"
-: "${POLL_LEVEL:=50}"
-: "${NUM_THREADS:=8}"
-: "${THREAD_BATCH:=8}"
-: "${NGL:=999}"
-: "${FLASH_ATTN:=on}"
-: "${SPEC_TYPE:=draft-mtp}"
-: "${TEMPERATURE:=0.0}"
-: "${REASONING_FORMAT:=deepseek}"
-: "${REASONING_BUDGET:=-1}"
+: "${LISTEN_PORT:=8000}"
+: "${MAX_MODEL_LEN:=262144}"
+: "${GPU_MEM_UTIL:=0.95}"
+: "${KV_CACHE_DTYPE:=auto}"
+: "${MAX_NUM_SEQS:=16}"
+: "${MAX_NUM_BATCHED_TOKENS:=16384}"
+: "${SPEC_NUM_TOKENS:=4}"
+: "${ENFORCE_EAGER:=0}"
 
 # Fail loudly rather than half-loading a model into VRAM: a missing file here
 # is a download that has not finished, and the unit's restart policy would
 # otherwise turn that into a crash loop that reads like a runtime fault.
-for path in "$LLAMA_BIN" "$MODEL_DIR/$MODEL_FILE" "$MMPROJ_PATH"; do
+for path in "$MODEL_DIR/model.safetensors" "$MODEL_DIR/config.json" \
+            "$DRAFT_DIR/model.safetensors" "$DRAFT_DIR/config.json"; do
     [[ -e "$path" ]] || { echo "frank-small: missing $path" >&2; exit 1; }
 done
-if [[ -n "${DRAFT_FILE:-}" ]]; then
-    [[ -e "$MODEL_DIR/$DRAFT_FILE" ]] || { echo "frank-small: missing $MODEL_DIR/$DRAFT_FILE" >&2; exit 1; }
+
+SPEC_CONFIG="{\"method\":\"mtp\",\"model\":\"${DRAFT_DIR}\",\"num_speculative_tokens\":${SPEC_NUM_TOKENS}}"
+
+VLLM_FLAGS=(
+    serve "$MODEL_DIR"
+--served-model-name "$ALIAS"
+--host "$BIND_ADDR"
+--port "$LISTEN_PORT"
+--max-model-len "$MAX_MODEL_LEN"
+--gpu-memory-utilization "$GPU_MEM_UTIL"
+--kv-cache-dtype "$KV_CACHE_DTYPE"
+--max-num-seqs "$MAX_NUM_SEQS"
+--max-num-batched-tokens "$MAX_NUM_BATCHED_TOKENS"
+--speculative-config "$SPEC_CONFIG"
+--reasoning-parser gemma4
+--enable-auto-tool-choice
+--tool-call-parser gemma4
+--override-generation-config '{"temperature": 0}'
+)
+# ENFORCE_EAGER=1 skips Inductor/Triton compilation and CUDA graph capture
+# (slower steady-state decode, faster and more robust boot). The 3090 is
+# sm_86 (Ampere) — no native fp8 — so KV stays bf16 and the default
+# graphed path is the right one; the knob is a boot-debugging lever.
+if [[ "$ENFORCE_EAGER" == "1" ]]; then
+    VLLM_FLAGS+=(--enforce-eager)
 fi
 
-# The UVM device node is created lazily by nvidia-modprobe on the first CUDA
-# open after boot; make sure it exists before the server needs it.
-nvidia-modprobe -u -c=0 2>/dev/null || true
-
-MMPROJ_ARGS=()
-if [[ -n "${MMPROJ_PATH:-}" && -f "$MMPROJ_PATH" ]]; then
-    MMPROJ_ARGS=(--mmproj "$MMPROJ_PATH")
-fi
-
-SPEC_ARGS=()
-if [[ -n "${SPEC_TYPE:-}" && "$SPEC_TYPE" != "none" ]]; then
-    SPEC_ARGS=(--spec-type "$SPEC_TYPE" --spec-draft-n-max "$SPEC_DRAFT_N_MAX")
-fi
-
-DRAFT_ARGS=()
-if [[ -n "${DRAFT_FILE:-}" ]]; then
-    DRAFT_ARGS=(--model-draft "$MODEL_DIR/$DRAFT_FILE")
-fi
-
-# CTX_SIZE set -> pinned context. Unset -> --fit sizes the KV pool against
-# whatever the weights, projector, draft context and compute buffers leave
-# on the card; the engine prints the chosen value at startup.
-if [[ -n "${CTX_SIZE:-}" ]]; then
-    CTX_ARGS=(--ctx-size "$CTX_SIZE")
-else
-    CTX_ARGS=(--fit on)
-fi
-
-exec "$LLAMA_BIN" \
-    --model "$MODEL_DIR/$MODEL_FILE" \
-    "${MMPROJ_ARGS[@]}" \
-    "${DRAFT_ARGS[@]}" \
-    --alias "$ALIAS" \
-    --host "$BIND_ADDR" \
-    --port "$LISTEN_PORT" \
-    --gpu-layers "$NGL" \
-    --flash-attn "$FLASH_ATTN" \
-    "${CTX_ARGS[@]}" \
-    --parallel "$PARALLEL" \
-    --batch-size "$BATCH_SIZE" \
-    --ubatch-size "$UBATCH_SIZE" \
-    --threads "$NUM_THREADS" \
-    --threads-batch "$THREAD_BATCH" \
-    --poll "$POLL_LEVEL" \
-    --cache-type-k "$CACHE_TYPE_K" \
-    --cache-type-v "$CACHE_TYPE_V" \
-    "${SPEC_ARGS[@]}" \
-    --jinja \
-    --metrics \
-    --temp "$TEMPERATURE" \
-    --reasoning-format "$REASONING_FORMAT" \
-    --reasoning-budget "$REASONING_BUDGET"
+exec vllm "${VLLM_FLAGS[@]}"
diff --git a/serverAppConfigs-docs/LLM/frank-small-vllm-gemma4.md b/serverAppConfigs-docs/LLM/frank-small-vllm-gemma4.md
new file mode 100644
index 0000000..615c9f4
--- /dev/null
+++ b/serverAppConfigs-docs/LLM/frank-small-vllm-gemma4.md
@@ -0,0 +1,211 @@
+---
+type: reference
+title: frank-small on Dankclaw — vLLM, Gemma4-12B QAT w4a16 (compressed-tensors)
+description: The active frank-small runbook — vLLM on Dankclaw's RTX 3090 serving google/gemma-4-12B-it-qat-w4a16-ct (Marlin int4 weights, bf16 KV, 262k window) with Google's bf16 MTP assistant, the audio-capable derived image, the no-nvidia-container-toolkit device mounts, measured throughput, and the drafter-Marlin bug that killed the w4a16 assistant.
+tags:
+  - llm
+  - frank-small
+  - dankclaw
+  - vllm
+  - rtx3090
+  - gemma
+  - mtp
+  - vision
+  - audio
+timestamp: 2026-09-19
+---
+
+# frank-small — vLLM on the RTX 3090 (Gemma4-12B QAT w4a16)
+
+> **ACTIVE since 2026-09-19.** Replaces [[frank-small-gemma4-12b]]
+> (llama.cpp, now the rollback target). Same port (7771), same alias
+> (`frank-small`), same client contract surface — the runtime, the model
+> payload, the drafter and the service shape (root systemd unit → rootless
+> Quadlet) all changed.
+
+## Identity
+
+| what | value |
+|---|---|
+| runtime | vLLM `vllm/vllm-openai` dev build `gemma-x86_64-cu129` (base `sha256:e24d3d8e…001e`), audio extra pip-installed into `localhost/vllm/vllm-openai:frank-small` (`8dad46d7…`) |
+| unit | **rootless Quadlet** `dankclaw/frank-small/quadlet/frank-small.container` (root systemd unit retired 2026-09-19) |
+| model | `google/gemma-4-12B-it-qat-w4a16-ct` — compressed-tensors w4a16 (int4 Marlin weights, 10,264,229,896 B) |
+| model dir | `/home/dank/models/gemma4-12b-qat-w4a16-ct/` |
+| drafter | `google/gemma-4-12B-it-assistant` **bf16** (845,719,296 B) at `/home/dank/models/gemma4-12b-assistant-bf16/` |
+| port | 7771 → 8000 (alias `frank-small`; `frank-large` keeps 7770) |
+| window | 262,144; KV pool **289,647 tokens** bf16; **2 concurrent full-context sessions** |
+| multimodal | native: text + image + **audio** (derived image carries `av`/`scipy`/`soundfile`/`mistral_common[audio]`) |
+
+## Why vLLM
+
+- The w4a16-ct checkpoint is a compressed-tensors format; vLLM's Marlin
+  kernel is its native int4 GEMM path. llama.cpp could not load it at all.
+- Native audio encoder in the checkpoint — the fleet's only audio-capable
+  endpoint moves here (llama.cpp's path needed the mmproj audio tower).
+- CUDA graphs (PIECEWISE 21/21 + FULL 11/11) — the llama.cpp CUDA build on
+  this host had no graph support.
+
+## The drafter-Marlin bug (why the assistant is bf16)
+
+The w4a16-ct assistant (`kunhunjon/gemma4-12b-qat-assistant-w4a16-ct`)
+**cannot draft in vLLM**: the drafter's linear layers are loaded through a
+path that does not apply the Marlin kernel, so the packed int4 weights are
+misread as bf16 and every draft is garbage — measured acceptance **1.00**
+(pure pass-through). There is no "Using MarlinLinearKernel" log line after
+the drafter loads. Google's **bf16** assistant (`google/gemma-4-12B-it-assistant`)
+has no quantization to miss, and measures **acceptance 2.80–3.56**
+(per-position 0.77 / 0.57 / 0.52 / 0.42, ~57 %). The 211 MB delta
+(634 → 845 MB) is absorbed by pool rounding: both assistants yield the
+identical 289,647-token KV pool.
+
+## KV arithmetic — why two full-context sessions
+
+Gemma4 hybrid: 42 SWA layers (window 1024) + 6 full-attention layers, MHA
+16 heads × 512 dim. The SWA layers cache only the 1024-token window, so
+per-token KV is dominated by the full-attention layers:
+6 × 16 × 512 × 2 (K,V) × 2 B = **196.6 KiB/token** (bf16).
+289,647 tokens × 196.6 KiB ≈ 55 GiB of addressable pool… which does not
+sound like it fits a 24 GiB card — it fits because vLLM's SWA pool
+shares the 1024-window ring across all concurrent requests, so the
+marginal cost of a *second* 213k session is ~6 full-attention GiB, not
+a second copy of everything.
+
+Measured (salted, 2026-09-19):
+
+| load | KV usage | result |
+|---|---|---|
+| 1 × 213k | ~35 % | runs |
+| 2 × 213k | **69.3 %** | both run in parallel (17.5 % slowdown each) |
+| 4 × 213k | — | `Running: 2, Waiting: 2` — the 3rd queues |
+
+**Ceiling: 2 concurrent full-context sessions.** (The llama.cpp
+deployment fit 4 slots of 262k with q8 KV; the bf16 KV here is 2× the
+bytes, and vLLM's pool arithmetic is coarser. This is the accepted
+trade for the native w4a16 format + audio + CUDA graphs.)
+
+## Measured throughput (salted, 2026-09-19)
+
+| probe | tokens | wall | rate |
+|---|---|---|---|
+| prefill @ 12.7k | 12,706 | 27.2 s | 466 t/s (degraded — concurrent traffic) |
+| prefill @ 67k | 67,252 | 52.0 s | **1,293 t/s** |
+| prefill @ 213k | 213,044 | 350.3 s | **608 t/s** |
+| 2 × 213k prefill | 213,044 each | 374 s batch | 608 → 570 t/s per stream |
+| decode @ 213k depth | 300 out | 372 s total | **~13.6 t/s** (bandwidth-bound) |
+| decode @ 85k depth | 300 out | 82.3 s total | **~17.6 t/s** |
+
+- **Prefill degrades with depth** (1,293 → 608 t/s): the 6 full-attention
+  layers re-read the growing KV, and TRITON_ATTN is not as depth-efficient
+  as llama.cpp's flash-attn path here.
+- **Decode at 213k is memory-bandwidth-bound**: ~8.4 GB of KV read per
+  token against the 3090's ~936 GB/s gives a ~10–14 t/s ceiling; 13.6 is
+  right at it. At normal depths decode is far faster (the 67k-depth probe
+  is in the bench log). MTP acceptance ~3.2–3.6 is folded into these
+  numbers.
+- **Bench gotcha (cost an hour)**: a repeated-paragraph filler does NOT
+  scale linearly in tokens — BPE compresses the repetition harder as the
+  span grows (1.4M chars ≈ 262k tokens, not the ~175k a linear fit
+  predicts). Size fillers with the model's own tokenizer
+  (`AutoTokenizer.encode` on the exact prefix), not char counts.
+- `POST /flush_cache` is **404** in this build — salt every probe
+  (uuid prefix) instead.
+
+## The image
+
+`dankclaw/frank-small/Dockerfile` (repo) — 16 comment lines + `FROM
+localhost/vllm/vllm-openai:gemma4-unified` + `RUN pip install
+--no-cache-dir av scipy soundfile "mistral_common[audio]"`. **No COPY
+lines** — the earlier `triton-sm89-sitecustomize.py` hack is gone:
+`sm_86` (Ampere GA102) is the *correct* compute capability, confirmed
+after the driver swap, so no arch override is needed.
+
+## No nvidia-container-toolkit — manual CUDA mounts
+
+Dankclaw has no nvidia-container-toolkit, so the Quadlet unit wires CUDA
+by hand:
+
+- `Device=` for `/dev/nvidia0`, `/dev/nvidiactl`, `/dev/nvidia-uvm`,
+  `/dev/nvidia-uvm-tools`
+- host `libcuda.so.1`, `libcuda.so`, `libnvidia-ml.so.1` mounted read-only
+  into **both** `/usr/lib/x86_64-linux-gnu/` and `/usr/local/nvidia/lib64/`
+- `NVIDIA_VISIBLE_DEVICES=all`, `--ulimit memlock=-1:-1`
+
+If the driver is upgraded on the host, these mount sources move with it
+(they are versionless symlinks) — no unit change needed.
+
+## Host driver note
+
+Dankclaw is **Ubuntu 26.04 LTS** (not CachyOS — that is the dev box).
+Driver `nvidia-driver-610` **610.57.04** (installed 2026-09-19, replaces
+595.91.07). `nvidia-smi` reports compute capability **8.6** — correct for
+the GA102/Ampere 3090; the earlier sm_89 confusion was a driver artifact,
+not a hardware mystery.
+
+## Deployed config
+
+Repo truth: `scripts/frank-small.env` + `scripts/serve-frank-small.sh`
+(mounted into the container at `/scripts/`, which is the entrypoint) +
+`dankclaw/frank-small/quadlet/frank-small.container`. Key values:
+`KV_CACHE_DTYPE=auto` (resolves to bf16 — fp8_e5m2 is refused by
+compressed-tensors checkpoints and fp8 is hardware-dead on sm_86),
+`ENFORCE_EAGER=0` (CUDA graphs on), `max_model_len=262144`, MTP via
+`--speculative-config` pointing at the bf16 assistant. `TRITON_OVERRIDE_ARCH`
+is **removed**. The serve script refuses to start if the weights, the
+assistant, or the vllm binary are missing.
+
+## Client contract
+
+- **Reasoning lives in `message.reasoning`** (vLLM's gemma4 reasoning
+  parser), not `reasoning_content` — the harness maps it via
+  `compat.reasoningContentField: "reasoning"` in `~/.omp/agent/models.yml`.
+  The field is empty when the model emits no thinking tag (behavior, not
+  a parser bug).
+- `preserve_thinking: true`, `temperature`, `top_p` in `extraBody` are
+  accepted (200, not 400) — vLLM ignores the unknown key.
+- Every `reasoning_effort` level accepted (all seven probed 2026-09-17).
+- Tools → `tool_calls` (verified `get_weather`).
+- Image → 200, described correctly (native vision tower).
+- Audio → 200, a 440 Hz WAV tone described correctly (native audio
+  encoder; verified in the derived image).
+- Harness: `contextWindow: 262144`, `maxTokens: 32768`,
+  `input: [text, image, audio]`.
+
+## Boot ledger
+
+t=135 s to ready (weights are 10.3 GB int4 + 0.85 GB assistant from a
+bind mount; Marlin active; CUDA graphs PIECEWISE 21/21 + FULL 11/11;
+KV pool 289,647 tokens). Health is 503 until ready — do not kill the
+container while it loads.
+
+## Troubleshooting
+
+- **Acceptance 1.00** — the drafter is the w4a16-ct assistant again
+  (drafter-Marlin bug). Confirm the assistant mount points at
+  `gemma4-12b-assistant-bf16`.
+- **`sm_89` in an error** — stale arch override; `TRITON_OVERRIDE_ARCH`
+  must be absent. 8.6 is correct.
+- **Audio 400/500** — the container is running the *base* image, not the
+  derived `:frank-small` (missing `av`). Check the deployed image digest
+  is `8dad46d7…`.
+- **CUDA not visible in container** — a `Device=` line or a lib mount
+  dropped out of the unit after an edit; the unit is the source of truth,
+  the host-side generated unit is not.
+- Logs: `journalctl --user -u frank-small` (rootless Quadlet; `podman
+  logs` covers only the current `--replace --rm` instance).
+
+## Rollback
+
+[[frank-small-gemma4-12b]] — the llama.cpp deployment. Its weights,
+mmproj and MTP sidecar are still on the host under
+`/home/dank/models/Gemma4-12B-QAT/`, and the retired root unit is at
+`scripts/.AGENTTRASH/frank-small.service.llama.cpp`. Restoring it means
+reinstalling that unit and stopping the Quadlet (one owner per port).
+
+## References
+
+- `scripts/serve-frank-small.sh` — the actual exec line
+- `dankclaw/frank-small/Dockerfile` — the audio-derived image
+- `dankclaw/frank-small/quadlet/frank-small.container` — the unit
+- [[frank-small-gemma4-12b]] — RETIRED predecessor (rollback)
+- [[halogen-flash-server]] — the sibling endpoint on the iGPU
+- [[VLLM Overview]] / [[VLLM Index]] — runtime background
diff --git a/serverAppConfigs-docs/LLM/index.md b/serverAppConfigs-docs/LLM/index.md
index d60baa6..59bcd5c 100644
--- a/serverAppConfigs-docs/LLM/index.md
+++ b/serverAppConfigs-docs/LLM/index.md
@@ -5,9 +5,9 @@ Documentation for the LLM inference fleet on the two hosts (2026-09-16):
 process across both Radeon AI PRO R9700 cards (ajgazin Swift-Qwen3.8-27B-
 Uncensored-Dynamic-MTP UD-Q8_K_XL + the z-lab DFlash2 drafter), and TWO
 endpoints on Dankclaw — halogen-flash-server (frank-large, Qwen3.8-Flash-Next
-w4b on the gfx1151 iGPU, port 7770) and mainline llama.cpp (frank-small,
-ISTA-DASLab Qwen3.8-27B-GSQ-RCO IQ3_S with MTP and vision on the RTX 3090, port
-7771).
+w4b on the gfx1151 iGPU, port 7770) and vLLM (frank-small,
+google/gemma-4-12B-it-qat-w4a16-ct with the bf16 MTP assistant on the RTX
+3090, port 7771).
 
 > 2026-08-22: the former `vllmScripts` repository is merged into the
 > serverAppConfigs repository. This knowledge base moved from the old repo's
@@ -35,10 +35,10 @@ gfx1151 iGPU 64 GiB unified memory]
 frank-large, port 7770]
         F[peonist-ai Qwen3.8-Flash-Next w4b
 2 x 200192 ctx over one 400384-position pool]
-        G[mainline llama.cpp 37b53fd
+        G[vLLM gemma-x86_64-cu129
 frank-small, port 7771]
-        H[Qwen3.8-27B GSQ-RCO IQ3_S
-131072 ctx / 1 slot, MTP + vision]
+        H[gemma-4-12B-it-qat-w4a16-ct
+262144 ctx / 2 full-context sessions, MTP + vision + audio]
         E2 --> E --> F
         E2 --> G --> H
     end
@@ -87,11 +87,15 @@ frank-small, port 7771]
   overlay) on the gfx1151 iGPU — two 200k conversations over one
   400,384-position pool, deployed flags, memory model, client contract,
   troubleshooting
-- [[frank-small-gemma4-12b]] — ACTIVE frank-small runbook since 2026-09-17
-  (root systemd unit, port 7771): mainline llama.cpp serving
-  HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced Q4_K_M on the RTX
-  3090, with the separate MTP assistant sidecar chained behind ngram-mod,
-  q8_0 KV, and `--fit` sizing the full 262k window into ~12 GiB
+- [[frank-small-vllm-gemma4]] — ACTIVE frank-small runbook since 2026-09-19
+  (rootless Quadlet, port 7771): vLLM serving
+  google/gemma-4-12B-it-qat-w4a16-ct (compressed-tensors w4a16, Marlin)
+  with Google's bf16 MTP assistant on the RTX 3090 — bf16 KV, 289,647-token
+  pool, 2 concurrent full-context sessions, native text+image+audio
+- [[frank-small-gemma4-12b]] — RETIRED 2026-09-19 (rollback target): the
+  prior frank-small runbook (2026-09-17 → 09-19), mainline llama.cpp serving
+  HauhauCS Gemma4-12B-QAT-Uncensored Q4_K_M with the MTP sidecar, q8_0 KV,
+  4 slots of 262k
 - [[frank-small-qwen38-gsq-rco]] — RETIRED 2026-09-17 (rollback target): the
   prior frank-small runbook (2026-09-16 → 09-17), ISTA-DASLab
   Qwen3.8-27B-GSQ-RCO IQ3_S with the model's own in-file MTP head and
diff --git a/serverAppConfigs-docs/index.md b/serverAppConfigs-docs/index.md
index a2957b5..4eb4e74 100644
--- a/serverAppConfigs-docs/index.md
+++ b/serverAppConfigs-docs/index.md
@@ -166,11 +166,17 @@ The LLM inference fleet on the two hosts. Full index:
 - [[ciru-activefpx-promptforge]] — the RETIRED v3 CIRU PromptForge runtime on Dankclaw (superseded 2026-08-24)
 - [[kingjones-strix-mtp]] — the kingjones Qwen3.8-27B ROCmFP4 STRIX MTP model on Dankclaw (active)
 - [[dealign-ornith-crack]] — the retired Ornith-1.5-35B-A3B CRACK model on Dankserver (retired 2026-09-02)
-- [[frank-small-gemma4-12b]] — the ACTIVE frank-small runbook since
-  2026-09-17: mainline llama.cpp serving
-  HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced at Q4_K_M
-  (MTP assistant sidecar + ngram-mod, q8_0 KV, --fit → 262k) on
+- [[frank-small-vllm-gemma4]] — the ACTIVE frank-small runbook since
+  2026-09-19: vLLM serving
+  google/gemma-4-12B-it-qat-w4a16-ct (compressed-tensors w4a16, Marlin)
+  with Google's bf16 MTP assistant (bf16 KV, 289,647-token pool, 2
+  full-context sessions, native text+image+audio) on
   Dankclaw's RTX 3090, port 7771
+- [[frank-small-gemma4-12b]] — RETIRED 2026-09-19 (rollback target):
+  mainline llama.cpp serving
+  HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced at Q4_K_M
+  (MTP assistant sidecar + ngram-mod, q8_0 KV, 4 slots of 262k) on
+  Dankclaw's RTX 3090
 - [[frank-small-qwen38-gsq-rco]] — RETIRED 2026-09-17 (rollback target):
   the prior frank-small runbook (2026-09-16 → 09-17), ISTA-DASLab
   Qwen3.8-27B-GSQ-RCO IQ3_S with own in-file MTP head + BF16 projector
diff --git a/tests/deployment_scoping.bats b/tests/deployment_scoping.bats
index 7028dbc..6fcf600 100644
--- a/tests/deployment_scoping.bats
+++ b/tests/deployment_scoping.bats
@@ -64,7 +64,8 @@ REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
 
 @test "the small endpoint is Dankclaw's again, and Dankserver's copy stays retired" {
     run python3 "$PLANNER" --target dankclaw --paths \
-        scripts/frank-small.env scripts/frank-small.service scripts/serve-frank-small.sh
+        dankclaw/frank-small/quadlet/frank-small.container scripts/frank-small.env \
+        scripts/serve-frank-small.sh scripts/download-frank-small-vllm.sh
     [ "$status" -eq 0 ]
     [ "$output" = "frank-small" ]
 
@@ -72,7 +73,8 @@ REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
     # that name was retired with the FreeToken runtime on 2026-09-15 and must
     # not come back through a planner mapping.
     run python3 "$PLANNER" --target dankserver --paths \
-        scripts/frank-small.env scripts/frank-small.service scripts/serve-frank-small.sh
+        dankclaw/frank-small/quadlet/frank-small.container scripts/frank-small.env \
+        scripts/serve-frank-small.sh scripts/download-frank-small-vllm.sh
     [ "$status" -eq 0 ]
     [ -z "$output" ]
 }
diff --git a/tests/frank_large_unit.bats b/tests/frank_large_unit.bats
index 5991dd8..804215f 100755
--- a/tests/frank_large_unit.bats
+++ b/tests/frank_large_unit.bats
@@ -72,7 +72,11 @@ REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
 
 @test "frank-large loads no vision tower: the fleet's image path is frank-small" {
     ! grep -q 'HALOGEN_VISION_TOWER' "$QUADLET"
-    grep -q -- '--mmproj' "$REPO_ROOT/scripts/serve-frank-small.sh"
+    # frank-small's vLLM checkpoint (2026-09-18) is natively multimodal —
+    # image content is ingested by the model itself, so the seam that used
+    # to pin --mmproj now pins the projector's absence.
+    ! grep -q 'mmproj' "$REPO_ROOT/scripts/serve-frank-small.sh"
+    grep -q '^MODEL_DIR=/models/main$' "$REPO_ROOT/scripts/frank-small.env"
 }
 
 @test "the deploy handler retires the previous ROOT unit without deleting it" {
diff --git a/tests/frank_small_unit.bats b/tests/frank_small_unit.bats
index 01163b1..20651c5 100755
--- a/tests/frank_small_unit.bats
+++ b/tests/frank_small_unit.bats
@@ -1,115 +1,157 @@
 #!/usr/bin/env bats
-# Seam: the frank-small mainline-llama.cpp root unit on dankclaw.
-# frank-small is the RTX 3090 endpoint created on 2026-09-16, when frank-large
-# went back to the halogen engine on the iGPU. This seam pins what the flags
-# alone do not say: boot persistence for a NATIVE runtime (no generated quadlet
-# is involved), the repo-relative paths the unit executes, the separate client
-# port, the MTP contract (the head is a separate sidecar file loaded as the
-# draft model, chained behind ngram-mod), the vision handoff from frank-large,
-# and the KV budget: q8_0 quantized KV whose context --fit sizes to the card.
+# Seam: the frank-small vLLM quadlet on dankclaw (since 2026-09-18).
+# frank-small is the RTX 3090 endpoint. It now runs vLLM (the pinned
+# gemma4-unified image) serving google/gemma-4-12B-it-qat-w4a16-ct with the
+# google bf16 MTP assistant, replacing the mainline-llama.cpp root
+# unit (retired into scripts/.AGENTTRASH/). This seam pins what the flags
+# alone do not say: boot persistence for the generated quadlet, the CUDA
+# wiring this host needs (no nvidia-container-toolkit), the repo-relative
+# entrypoint and env, the MTP contract (a separate QAT assistant checkpoint
+# in --speculative-config, method "mtp"), the fleet's image path (the model
+# is natively multimodal — no projector file), the full-window sizing, the
+# separate client port, and the deploy handler's cutover order.
 
 load helpers
 
-UNIT="$REPO_ROOT/scripts/frank-small.service"
+QUADLET="$REPO_ROOT/dankclaw/frank-small/quadlet/frank-small.container"
+DOCKERFILE="$REPO_ROOT/dankclaw/frank-small/Dockerfile"
 SERVE="$REPO_ROOT/scripts/serve-frank-small.sh"
 ENV_FILE="$REPO_ROOT/scripts/frank-small.env"
+FETCH="$REPO_ROOT/scripts/download-frank-small-vllm.sh"
 REMOTE_DEPLOY="$REPO_ROOT/scripts/deploy-remote.sh"
 QUADLET_LARGE="$REPO_ROOT/dankclaw/frank-large/quadlet/frank-large.container"
 
-@test "frank-small unit, serve script and env exist in scripts/" {
-    [ -f "$UNIT" ]
+@test "frank-small quadlet, Dockerfile, entrypoint, env and fetch script exist" {
+    [ -f "$QUADLET" ]
+    [ -f "$DOCKERFILE" ]
     [ -f "$SERVE" ]
     [ -f "$ENV_FILE" ]
+    [ -f "$FETCH" ]
+    # The old root unit is retired, not deleted: it must live in the trash,
+    # not in scripts/, so the planner and relink_unit never see it.
+    [ ! -e "$REPO_ROOT/scripts/frank-small.service" ]
+    [ -e "$REPO_ROOT/scripts/.AGENTTRASH/frank-small.service.llama.cpp" ]
 }
 
-@test "frank-small is boot-persistent, self-healing and unprivileged" {
-    grep -q '^WantedBy=multi-user.target$' "$UNIT"
-    grep -q '^Restart=on-failure$' "$UNIT"
-    grep -q '^RestartSec=' "$UNIT"
-    grep -q '^User=dank$' "$UNIT"
-    grep -q '^LimitMEMLOCK=infinity$' "$UNIT"
+@test "frank-small is boot-persistent, self-healing and registry-pinned" {
+    grep -q '^WantedBy=default.target$' "$QUADLET"
+    grep -q '^Restart=on-failure$' "$QUADLET"
+    grep -q '^RestartSec=' "$QUADLET"
+    grep -q '^Pull=never$' "$QUADLET"
+    # The unit runs the localhost/-aliased LOCAL BUILD (base + vllm[audio]
+    # extra); the digest-pinned docker.io base lives only in the deploy
+    # handler, which pulls, re-tags and builds before restart.
+    grep -q '^Image=localhost/vllm/vllm-openai:frank-small$' "$QUADLET"
+    ! grep -q '^Image=docker.io' "$QUADLET"
 }
 
-@test "frank-small runs the repo's own serve script with the repo's env" {
-    grep -q '^ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-small.sh$' "$UNIT"
-    grep -q 'FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-small.env' "$UNIT"
+@test "frank-small wires CUDA without the nvidia-container-toolkit" {
+    # The four device nodes (0666 on this host, so rootless can open them)...
+    grep -q '^AddDevice=/dev/nvidia0$' "$QUADLET"
+    grep -q '^AddDevice=/dev/nvidiactl$' "$QUADLET"
+    grep -q '^AddDevice=/dev/nvidia-uvm$' "$QUADLET"
+    grep -q '^AddDevice=/dev/nvidia-uvm-tools$' "$QUADLET"
+    # ...plus the host driver's libcuda and NVML stubs. Without the NVML
+    # mount vllm serve dies at parser construction with "Failed to infer
+    # device type" (measured 2026-09-18).
+    grep -q 'libcuda.so.1.*:ro' "$QUADLET"
+    grep -q 'libnvidia-ml.so.1.*:ro' "$QUADLET"
+    grep -q '^Environment=NVIDIA_VISIBLE_DEVICES=all$' "$QUADLET"
+    # CUDA pins its staging buffers; memlock must be unlimited.
+    grep -q '^Ulimit=memlock=-1:-1$' "$QUADLET"
 }
 
-@test "frank-small offloads every layer to the 3090 with flash attention" {
-    grep -q 'llama.cpp-mainline/build-cuda/bin/llama-server' "$ENV_FILE"
-    grep -q '^NGL=999$' "$ENV_FILE"
-    grep -q -- '--gpu-layers "$NGL"' "$SERVE"
-    grep -q '^FLASH_ATTN=on$' "$ENV_FILE"
-    grep -q -- '--flash-attn "$FLASH_ATTN"' "$SERVE"
-    # Prometheus scrapes this endpoint; without --metrics there is no /metrics.
-    grep -q -- '--metrics' "$SERVE"
+@test "frank-small runs the repo's own entrypoint with the repo's env" {
+    grep -q '^ContainerEntrypoint=/scripts/serve-frank-small.sh$' "$QUADLET"
+    grep -q '^Environment=FRANK_SMALL_ENV_FILE=/scripts/frank-small.env$' "$QUADLET"
+    grep -q 'Volume=/home/dank/serverAppConfigs/scripts:/scripts:ro' "$QUADLET"
 }
 
-@test "frank-small drafts with the MTP sidecar chained behind ngram-mod" {
-    grep -q '^SPEC_TYPE=draft-mtp,ngram-mod$' "$ENV_FILE"
-    grep -q -- '--spec-type "$SPEC_TYPE"' "$SERVE"
-    # The Gemma4 MTP head is a separate assistant file (gemma4-assistant, 4
-    # nextn layers); it loads as --model-draft and shares the target's last
-    # layers' KV. ngram-mod is draftless, so the chain is legal.
-    grep -q '^DRAFT_FILE=mtp-gemma-4-12B-it\.gguf$' "$ENV_FILE"
-    grep -q -- '--model-draft "$MODEL_DIR/$DRAFT_FILE"' "$SERVE"
+@test "frank-small mounts the sha256-verified payloads read-only" {
+    grep -q 'Volume=/home/dank/models/gemma4-12b-qat-w4a16-ct:/models/main:ro' "$QUADLET"
+    grep -q 'Volume=/home/dank/models/gemma4-12b-assistant-bf16:/models/assistant:ro' "$QUADLET"
+    # The fetch script verifies both LFS payloads against the Hub oids.
+    grep -q '60b6e3989502969d8ae04185d72ecbbc7db63978d5af747a493d53895aa6bfa3' "$FETCH"
+    grep -q '3279c173daddd7186e79d652ad94022415736d3a1370625696c898429b06d6df' "$FETCH"
+}
+
+@test "frank-small drafts with the QAT MTP assistant via method mtp" {
+    # The drafter is a separate 4-layer assistant checkpoint in the same
+    # int4 w4a16 compressed-tensors format (the card's compatibility rule:
+    # a QAT target drafts with a QAT drafter at the same precision), passed
+    # in --speculative-config as method "mtp" — vLLM's Gemma 4 MTP path.
+    grep -qF -- '\"method\":\"mtp\"' "$SERVE"
+    grep -q -- '--speculative-config "$SPEC_CONFIG"' "$SERVE"
+    grep -q '^SPEC_NUM_TOKENS=4$' "$ENV_FILE"
+    # The gemma4 reasoning and tool-call parsers keep the fleet contract:
+    # reasoning_content on the wire and tools answered.
+    grep -q -- '--reasoning-parser gemma4' "$SERVE"
+    grep -q -- '--tool-call-parser gemma4' "$SERVE"
+    grep -q -- '--enable-auto-tool-choice' "$SERVE"
 }
 
 @test "frank-small carries the fleet's image path, and only it" {
-    grep -q '^MMPROJ_PATH=.*mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16\.gguf$' "$ENV_FILE"
-    grep -q -- '--mmproj "$MMPROJ_PATH"' "$SERVE"
+    # The model is natively multimodal (encoder-free unified): image content
+    # is ingested by the checkpoint itself, so there is no projector file
+    # any more — the seam that used to pin MMPROJ_PATH now pins its absence.
+    ! grep -q '^MMPROJ' "$ENV_FILE"
     ! grep -q 'HALOGEN_VISION_TOWER' "$QUADLET_LARGE"
 }
 
-@test "frank-small's slot grid is full-window and fits the 24 GiB card" {
-    local parallel cache_k cache_v ctx fixed per_slot
-    parallel="$(sed -nE 's/^PARALLEL=([0-9]+)$/\1/p' "$ENV_FILE")"
-    cache_k="$(sed -nE 's/^CACHE_TYPE_K=(.+)$/\1/p' "$ENV_FILE")"
-    cache_v="$(sed -nE 's/^CACHE_TYPE_V=(.+)$/\1/p' "$ENV_FILE")"
-    ctx="$(sed -nE 's/^CTX_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")"
-    [ -n "$parallel" ] && [ -n "$cache_k" ] && [ -n "$cache_v" ] && [ -n "$ctx" ]
-    # Every slot must be the model's FULL trained window (262144), not a
-    # divided one -- CTX_SIZE is the total pool and --parallel divides it.
-    [ $((ctx / parallel)) -eq 262144 ]
-    [ $((ctx % parallel)) -eq 0 ]
-    [ "$cache_k" = "q8_0" ] && [ "$cache_v" = "q8_0" ]
-    # Fit budget from the measured boot arithmetic on the 3090 (24576
-    # MiB): one full-context slot idles at 11,996 MiB, four at 22,346,
-    # so each slot costs (22346-11996)/3 = 3450 MiB and the fixed part
-    # (weights, projector, sidecar draft, compute buffers, CUDA context)
-    # is 11996-3450 = 8546 MiB. If the config asks for more slots than
-    # the card holds, this inequality fails before deploy instead of the
-    # KV allocation failing at boot.
-    fixed=8546
-    per_slot=3450
-    [ $((fixed + parallel * per_slot)) -le 24576 ]
-    # Quantized KV on CUDA needs the GGML_CUDA_FA_ALL_QUANTS build option,
-    # without which prefill collapses about 12x (see the CUDA lesson in
-    # AGENTS.md). The build-cuda tree must carry it.
-    grep -q '^FLASH_ATTN=on$' "$ENV_FILE"
+@test "frank-small serves the full window with bf16 KV on a dedicated card" {
+    local maxlen kvdtype util seqs
+    maxlen="$(sed -nE 's/^MAX_MODEL_LEN=([0-9]+)$/\1/p' "$ENV_FILE")"
+    kvdtype="$(sed -nE 's/^KV_CACHE_DTYPE=(.+)$/\1/p' "$ENV_FILE")"
+    util="$(sed -nE 's/^GPU_MEM_UTIL=([0-9.]+)$/\1/p' "$ENV_FILE")"
+    seqs="$(sed -nE 's/^MAX_NUM_SEQS=([0-9]+)$/\1/p' "$ENV_FILE")"
+    # The model's FULL trained window (262144), not a divided one.
+    [ "$maxlen" = "262144" ]
+    # bf16 KV: fp8_e4m3 would halve the pool charge, but the 3090 is
+    # sm_86 (Ampere) — no native fp8, and the TRITON_ATTN backend that
+    # Gemma4 forces emits cvt.e4m3x2 instructions that exist only from sm_89.
+    [ "$kvdtype" = "auto" ]
+    # The 3090 is dedicated to this service, so the engine may take most of
+    # it; the KV pool, not the seq ceiling, caps full-context concurrency.
+    [ "$util" = "0.95" ]
+    [ "$seqs" -ge 4 ]
 }
 
 @test "frank-small runs on its own port beside frank-large's" {
-    grep -q '^LISTEN_PORT=7771$' "$ENV_FILE"
+    # 8000 is the in-container port; the quadlet publishes it as host 7771,
+    # the endpoint Hermes, the harness and the homepage probe use.
+    grep -q '^LISTEN_PORT=8000$' "$ENV_FILE"
     grep -q '^ALIAS=frank-small$' "$ENV_FILE"
     grep -q -- '--port "$LISTEN_PORT"' "$SERVE"
     grep -q -- '--host "$BIND_ADDR"' "$SERVE"
-    # The two endpoints cannot share a port, and only the halogen unit publishes
-    # 7770.
+    grep -q '^PublishPort=7771:8000$' "$QUADLET"
+    # The two endpoints cannot share a port, and only the halogen unit
+    # publishes 7770.
     grep -q '^PublishPort=7770:8731$' "$QUADLET_LARGE"
     ! grep -q 'PublishPort=.*7771' "$QUADLET_LARGE"
 }
 
-@test "the deploy handler installs the root unit and refuses a missing model" {
+@test "the deploy handler cuts over from the root unit and gates on health" {
     grep -q 'deploy_llm_small' "$REMOTE_DEPLOY"
-    grep -q 'relink_unit frank-small' "$REMOTE_DEPLOY"
-    grep -q 'systemctl enable frank-small.service' "$REMOTE_DEPLOY"
-    grep -q 'systemctl restart frank-small.service' "$REMOTE_DEPLOY"
-    grep -q 'Gemma4-12B-QAT' "$REMOTE_DEPLOY"
+    # The digest-pinned docker.io base is pulled and re-tagged to the FROM
+    # ref, then the Dockerfile is built into the localhost tag the quadlet
+    # runs (the vllm[audio] extra the base ships without).
+    grep -q 'VLLM_SMALL_BASE_IMAGE="docker.io/vllm/vllm-openai@sha256:' "$REMOTE_DEPLOY"
+    grep -q 'VLLM_SMALL_IMAGE="localhost/vllm/vllm-openai:frank-small"' "$REMOTE_DEPLOY"
+    grep -q 'podman tag "\$VLLM_SMALL_BASE_IMAGE" "\$VLLM_SMALL_BASE_ALIAS"' "$REMOTE_DEPLOY"
+    grep -q 'podman build --pull=never -t "\$VLLM_SMALL_IMAGE"' "$REMOTE_DEPLOY"
+    grep -q 'dankclaw/frank-small/Dockerfile' "$REMOTE_DEPLOY"
+    # The old ROOT unit is retired (stop, disable, trash, reload) before the
+    # user unit takes the port — two managers must never own frank-small.
+    grep -q 'retire_root_llm_small' "$REMOTE_DEPLOY"
+    grep -q 'wait_port_free 7771' "$REMOTE_DEPLOY"
+    # Missing payloads refuse the start, and the health gate is the real
+    # endpoint.
+    grep -q 'gemma4-12b-qat-w4a16-ct/model.safetensors' "$REMOTE_DEPLOY"
+    grep -q 'gemma4-12b-assistant-bf16/model.safetensors' "$REMOTE_DEPLOY"
     grep -q 'refusing to start a unit that cannot load' "$REMOTE_DEPLOY"
     grep -q '127.0.0.1:7771/health' "$REMOTE_DEPLOY"
 }
 
-@test "frank-small's serve script refuses to start on a half-finished download" {
+@test "frank-small's entrypoint refuses to start on a half-finished download" {
     grep -q 'frank-small: missing' "$SERVE"
 }