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Build Baidu ERNIE-Image / ERNIE-Image-Turbo workflows — primarily TEXT-TO-IMAGE. Pick ERNIE when you need precise multilingual text rendering, posters/signage, manga/anime multi-panel layouts, or strong instruction following for complex multi-object scenes. Also supports denoise-based image-to-image refine (NOT instruction-grounded editing — use Qwen-Image-Edit or Flux Kontext for "change X in this photo" edits).
Passed 22 of 22 test cases with the skill, and 8 of 22 without it.
and 17 more in the full report
14 fixed8 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am configuring a ComfyUI workflow for ERNIE-Image-Turbo. The model directory contains both flux2-vae.safetensors and ae.safetensors. Which VAE file should be passed into the VAELoader for ERNIE-Image renders?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies flux2-vae.safetensors for ERNIE-Image. | Missed | Passed |
The instructions your model reads when the skill loads.
ERNIE-Image is Baidu's open-weight TEXT-TO-IMAGE model, an ~8B single-stream Diffusion Transformer (DiT), Apache-2.0, released April 2026 and repackaged for ComfyUI by Comfy-Org. It is not an instruction-based image editor.
ernie-image-turbo-*.gguf).Pick ERNIE when the job is precise text/typography rendering (multilingual, including Chinese), posters/signage/UI mockups, manga/anime storyboards and multi-panel layouts, or structured multi-object scenes from a complex prompt.
Do not pick ERNIE for "edit this photo / change the shirt / swap the background". That is instruction-grounded editing, which ERNIE does not do. Use qwen-image-edit or Flux Kontext for those. ERNIE's "image-to-image" here is plain denoise-based refinement (style pass / detail pass), not reference-grounded editing.
Niche vs siblings. ERNIE is the best open-weight text rendering + layout T2I. Qwen-Image-Edit does instruction editing. Flux Kontext does reference editing. Z-Image Turbo does fast general T2I, and this same pack pairs the two; see Combo pipelines.
The original ernie monolith was a single toggle-template graph (every pipeline shipped bypassed; you activated one via the rgthree group toggles). It's now split into standalone, single-purpose packs, each a clean activated graph that renders headlessly with no group-toggling:
| Pack | Use | Models | VRAM |
|---|---|---|---|
ernie-txt2img | text-to-image (flagship) | ERNIE only (4) | <8GB |
ernie-img2img | denoise refine of a source image | ERNIE only (4) | <8GB |
ernie-combo | ERNIE × Z-Image-Turbo combo pipelines | ERNIE + Z-Image (7, ~32GB) | 12GB+ |
Working details verified live: the prompt-enhancer LLM is OFF by default (the ENHANCE PROMPT boolean is false; leave it off unless you want the 3B enhancer to rewrite the prompt). The grain/sharpen post-proc (FastFilmGrain/FastLaplacianSharpen, comfyui-vrgamedevgirl) needs librosa installed. In ernie-combo the Z-Image half's VAE is saved as z-image-ae.safetensors; its weights differ from Flux/ERNIE's ae.safetensors despite the same size, and the rename avoids a filename clash.
This skill is derived from the actual pack files in C:\Users\Artokun\Downloads\:
ERNIE-IMAGE-ULTRA-WORKFLOW.json (authoritative; the ComfyUI graph)ERNIE-IMAGE_ULTRA-MODELS-NODES_INSTALL.bat, ...-COMFYUI-MANAGER_AUTO_INSTALL.bat, ...-AUTO_INSTALL-RUNPOD.shInstaller warning (verified). The three install scripts are copy-pasted from a Z-Image pack. Their headers literally say "Z-IMAGE-BASE"/"Z-IMAGE Base", and they download both ERNIE and Z-Image files. The model URLs/folders below are taken from those scripts but mirror this confusion. They pull
z_image_turbo-*.gguf,Qwen3-4B-*.gguf, andae.safetensors, which belong to the Z-Image half of the combo, not ERNIE. The ERNIE-only files are flagged below. All weights come from a third-party mirrorhuggingface.co/Aitrepreneur/FLX, not the officialhuggingface.co/Comfy-Org/ERNIE-Image(which hosts the same filenames; see Official sources).
Confirmed from the workflow's virtual wires (Set_*/GetNode): the nodes tagged "ERNIE" resolve to these exact files.
test cases passed, vs 8 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.