docs(vault): destroy the dead weight — 53 pages and the change diary
The vault was 155 pages / 31,210 lines, most of it measurement ledgers for payloads that no longer run. A throughput figure for a runtime nobody operates is not a record: AI moves faster than the vault, so the number is wrong before anyone reads it, and a wrong number in a runbook gets believed. Per the new purpose test in `AGENTS.md` → *Documentation Policy*, it is destroyed. Gone (`.AGENTTRASH/20261019-destruction/`, KILL-LIST.txt is the manifest): - the `frank-medium` endpoint and its five era pages, `frank-npu`, FastFlowLM, the ikllama/kingjones/dealign/frank-redo eras, the ling/swift15/freetoken/ubatch campaign pages, qwen3.8 spec-matrix and strix-optimizations, the two "Running Qwen3.6 …" pages; - the whole `Pipeline Parallelism/` folder (no live script passes a pipeline flag) and the multi-device/x4-pair/hybrid/offload experiment pages; - every vLLM page — no vLLM endpoint exists on this fleet; - `LLM/deployment.md` (`Architecture/Deployment Flow.md` is the test-referenced owner) and the external surveys (SGLang, Lemonade, llama.cpp forks/diff, self-hosted app census, the TTS survey) that were obsolete by construction; - `log.md`, 2,380 lines. Git holds the chronology; a causal law belongs to the page that owns the thing it governs, never to a diary. Survivors: 101 pages, 17,542 lines, 0 OKF violations, 0 unresolved links. Eras tables keep the window, payload, runtime, reason and rollback pointer; the rate columns are blanked. The live shapes stay verbatim — those numbers are what the deployer and `models.yml` consume.
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@@ -56,8 +56,8 @@ sampling), `sampler_name: euler`, `scheduler: simple`, `denoise: 1.0`, seed
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fixed in the file (`1930` in the art workflow, `2026` in the text one) —
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read from `dankclaw/comfyui/workflows/*.json` node `9`.
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Node `class_type`s in both files: `CLIPTextEncode` ×2, `UNETLoader`,
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`CLIPLoader`, `VAELoader`, `EmptySD3LatentImage`, `KSampler`, `VAEDecode`,
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Node `class_type`s in both files: `CLIPTextEncode` ×2, `UNETLoader`
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`CLIPLoader`, `VAELoader`, `EmptySD3LatentImage`, `KSampler`, `VAEDecode`
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`SaveImage` (ids 3–11).
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| Workflow | File | Shape | Steps | Made for |
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@@ -113,9 +113,9 @@ only `models`, `input`, `output`, `custom_nodes` and the healthcheck file
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Quantized preferred, sized for the 8060S iGPU (GTT-backed — `/system_stats`
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reports 122.4 GB of device VRAM on `cuda:0`, `curl http://127.0.0.1:8188/system_stats`
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2026-10-18; the RTX 3090 is frank-zealot's). All repos verified 2026-10-05 and
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all four still resolve today (`huggingface.co/lightx2v/Qwen-Image-Lightning`,
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`huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF`,
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`huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets`,
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all four still resolve today (`huggingface.co/lightx2v/Qwen-Image-Lightning`
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`huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF`
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`huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets`
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`huggingface.co/QuantStack/Wan2.2-TI2V-5B-GGUF`, 2026-10-18). None are on disk
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yet: `models/` holds no lora/, controlnet/ or Wan/Edit file (`ls -R` 2026-10-18).
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@@ -126,7 +126,7 @@ yet: `models/` holds no lora/, controlnet/ or Wan/Edit file (`ls -R` 2026-10-18)
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| 3 | **DiffSynth ControlNets** (structure control) | `Comfy-Org/Qwen-Image-DiffSynth-ControlNets` | `split_files/model_patches/` canny + depth | ~2–3 GB each | Pose/edge/depth-guided layouts — pairs with the legible-text workflow for exact poster composition. The `QwenImageDiffsynthControlnet` node is already in the running ComfyUI (`GET http://127.0.0.1:8188/object_info/QwenImageDiffsynthControlnet` → 200, 2026-10-18) |
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| 4 | **Wan 2.2 TI2V-5B GGUF** (first video model) | `QuantStack/Wan2.2-TI2V-5B-GGUF` | Q4/Q5 GGUF (~6–8 GB) | ~6–8 GB | T2V+I2V in one dense 5B model; the gentlest on-ramp into video generation, runs in ComfyUI core (`wan` is in this build's `CLIPLoader` type enum — `GET http://127.0.0.1:8188/object_info/CLIPLoader` 2026-10-18) |
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Placement: #1 → `models/lora/` (create it), #2 → `models/diffusion_models/`,
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Placement: #1 → `models/lora/` (create it), #2 → `models/diffusion_models/`
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#3 → `models/controlnet/` (create it), #4 → `models/diffusion_models/`.
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Fetch with `scripts/download-frank-*.sh` discipline (`-f` + byte-count +
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sha256 checks) or a plain `hf download` with the token in the environment —
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