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.
7.9 KiB
type, description, tags, timestamp
| type | description | tags | timestamp | |||
|---|---|---|---|---|---|---|
| howto | Proven Qwen-Image text-to-image workflows on Dankclaw: the recipes, the API call shape, and which models to add next. |
|
2026-10-05 |
ComfyUI Qwen-Image Workflows
Two ready-to-load text-to-image workflows for the Qwen-Image 2.1 payload
already on Dankclaw, both proven end-to-end on 2026-10-05 by POSTing to the
live API on port 8188 and verifying the rendered PNG (the renders are still on
disk: qwen21-art_00001_.png 22:41 and qwen21-text_00001_.png 22:44,
ls -l /home/dank/comfyui-data/output/ 2026-10-18). The repo copies are the
source of truth; the host copies under /home/dank/comfyui-data/workflows/
are for convenience and are byte-identical today (md5sum matches both files,
2026-10-18).
What is on disk
Sizes are GiB, measured ls -l on the host 2026-10-18 (all files dated
2026-09-21).
Path (under /home/dank/comfyui-data/models/) |
Size | Role |
|---|---|---|
diffusion_models/qwen_image_2.1_int8_convrot.safetensors |
6.8 GB (7,256,783,064 B) | The one the workflows use — int8-convrot quant, ComfyUI-core native |
diffusion_models/qwen_image_2.1_bf16.safetensors |
13.3 GB (14,230,280,616 B) | Full-precision fallback |
diffusion_models/qwen-image-2.1-Q8_0.gguf (+ -arch) |
7.1 GB each (7,591,551,648 / 7,591,551,680 B) | GGUF alternative (needs ComfyUI-GGUF custom node, present in custom_nodes/) |
text_encoders/qwen3vl_8b_w4a8.safetensors |
5.9 GB (6,312,105,364 B) | The one the workflows use — 4-bit-weights/8-bit-act Qwen3-VL 8B encoder |
text_encoders/qwen3vl_8b_int8_convrot.safetensors |
8.7 GB (9,350,798,360 B) | Mid quant |
text_encoders/qwen3vl_8b_bf16.safetensors |
16.3 GB (17,534,334,616 B) | Full precision |
vae/qwen_image_2.1_vae_bf16.safetensors |
645 MB (675,509,688 B) | 2.1 VAE (used) |
vae/qwen_image_vae.safetensors |
243 MB (253,806,246 B) | Smaller VAE |
No LoRAs are on disk yet, and models/lora/ / models/controlnet/ do not
exist — see Recommended additions.
The workflows
Both are API-format JSON (ComfyUI 0.37 loads them via the UI's Load dialog
too): dankclaw/comfyui/workflows/ in the repo,
/home/dank/comfyui-data/workflows/ on the host. Node chain in both:
UNETLoader (int8_convrot) ──┐
CLIPLoader (qwen_image, w4a8) ─┤ CLIPTextEncode pos/neg
VAELoader (2.1 bf16) ────────┤
EmptySD3LatentImage ─────────┴─ KSampler ─ VAEDecode ─ SaveImage
Common sampler settings: cfg 1.0 (Qwen-Image 2.1 expects CFG-free
sampling), sampler_name: euler, scheduler: simple, denoise: 1.0, seed
fixed in the file (1930 in the art workflow, 2026 in the text one) —
read from dankclaw/comfyui/workflows/*.json node 9.
Node class_types in both files: CLIPTextEncode ×2, UNETLoader
CLIPLoader, VAELoader, EmptySD3LatentImage, KSampler, VAEDecode
SaveImage (ids 3–11).
| Workflow | File | Shape | Steps | Made for |
|---|---|---|---|---|
| Art | qwen-image-2.1-t2i-art.json |
1024×1024 | 20 | General illustration/prose prompts |
| Legible text | qwen-image-2.1-t2i-legible-text.json |
832×1216 | 25 | Posters, captions, any in-image text |
Legible-text prompt recipe
Qwen-Image 2.1 is one of the best open-weight text renderers, but only if the prompt is written for it:
- Quote the exact strings:
large bold white text reading "SOLIDARITY OF THE SOVIET COMPUTER SYSTEMS"— quoted text is rendered literally. - Describe layout, not vibes: say centered / below it / large vs small, the typeface family (sans-serif), and the color.
- Say what NOT to draw: end with
no other words, no watermark. - Keep the negative side on
misspelled, warped letters, extra text(already in the workflow). - More steps help text: the text workflow uses 25 vs 20.
Verified render: SOLIDARITY OF THE SOVIET COMPUTER SYSTEMS + DANKCLAW DANKSERVER EST 2026 came back crisp and correctly spelled at 832×1216
(qwen21-text_00001_.png, 953,254 B — still on disk, ls -l /home/dank/comfyui-data/output/ 2026-10-18). One caveat from the same render:
a shorter secondary line is where misspellings creep in — proofread the first
render before shipping.
Driving it from the API
ComfyUI 0.37 requires the graph wrapped in a prompt key — a bare
{node-id: node} body gets {"error": {"type": "no_prompt"}} (verified
2026-10-05):
curl -s -X POST http://127.0.0.1:8188/prompt -H 'Content-Type: application/json' \
-d "$(python3 -c 'import json;print(json.dumps({"prompt": json.load(open("dankclaw/comfyui/workflows/qwen-image-2.1-t2i-art.json"))}))')"
# -> {"prompt_id": "...", ...}
curl -s http://127.0.0.1:8188/history/<prompt_id> # status.status_str == "success"
Outputs land in /home/dank/comfyui-data/output/. The queue is FIFO — the
two workflows above ran back-to-back unattended.
Note: the container's UI-saved workflows live in the ephemeral
/opt/ComfyUI/user layer and do NOT survive an image rebuild — the unit mounts
only models, input, output, custom_nodes and the healthcheck file
(podman inspect comfyui 2026-10-18; dankclaw/comfyui/quadlet/comfyui.container:48-52)
— hence the host-side workflows/ dir and the repo copy.
Recommended additions
Quantized preferred, sized for the 8060S iGPU (GTT-backed — /system_stats
reports 122.4 GB of device VRAM on cuda:0, curl http://127.0.0.1:8188/system_stats
2026-10-18; the RTX 3090 is frank-zealot's). All repos verified 2026-10-05 and
all four still resolve today (huggingface.co/lightx2v/Qwen-Image-Lightning
huggingface.co/unsloth/Qwen-Image-Edit-2511-GGUF
huggingface.co/Comfy-Org/Qwen-Image-DiffSynth-ControlNets
huggingface.co/QuantStack/Wan2.2-TI2V-5B-GGUF, 2026-10-18). None are on disk
yet: models/ holds no lora/, controlnet/ or Wan/Edit file (ls -R 2026-10-18).
| # | What | Repo | Grab | Size | Why |
|---|---|---|---|---|---|
| 1 | Lightning 8-step LoRA (T2I speed) | lightx2v/Qwen-Image-Lightning |
qwen_image_lightning_8steps_*.safetensors (LoRA) |
~1–2 GB | 20 steps → 8 with a LoraLoader node; 2–3× faster renders on the iGPU, negligible quality loss |
| 2 | Qwen-Image-Edit-2511 GGUF (image editing) | unsloth/Qwen-Image-Edit-2511-GGUF |
Q4_K_M (~13.2 GB) or Q4_0 (~11.9 GB) | ~12–13 GB | Unlocks img2img "edit this photo" workflows — a capability class the fleet has zero of; Q4 keeps it iGPU-friendly |
| 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) |
| 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) |
Placement: #1 → models/lora/ (create it), #2 → models/diffusion_models/
#3 → models/controlnet/ (create it), #4 → models/diffusion_models/.
Fetch with scripts/download-frank-*.sh discipline (-f + byte-count +
sha256 checks) or a plain hf download with the token in the environment —
never on the command line.
Skip list: the original city96/Qwen-Image-gguf conversions (superseded by
the 2.1 files already on disk), and any BF16 of #2/#4 (the iGPU does not need
them at GTT capacity, and they double the disk bill).
See Also
- ComfyUI — the service itself (image, unit, GPU access)
- ComfyUI ROCm and Vulkan — the live-verified GPU path
- Dankclaw Stack — the host