Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sandyup/comfyui-mcp --skill ernie-imagegit clone --depth 1 https://github.com/sandyup/comfyui-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sandyup/comfyui-mcp/ernie-image)<a href="https://agentmods.dev/skills/sandyup/comfyui-mcp/ernie-image"><img src="https://agentmods.dev/badge/skills/sandyup/comfyui-mcp/ernie-image/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sandyup/comfyui-mcp/ernie-image"><img src="https://agentmods.dev/badge/skills/sandyup/comfyui-mcp/ernie-image.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00098 | $0.05435 |
| Opus 5.5 | $0.00039 | $0.02174 |
| Sonnet 5.5 | $0.00020 | $0.01087 |
| Haiku 4.5 | $0.00010 | $0.00543 |
Grade A, and why
ernie-image scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
88% identical to ernie-image — 104 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ERNIE-Image / ERNIE-Image-Turbo Workflows
What this is (read first)
ERNIE-Image is Baidu's open-weight TEXT-TO-IMAGE model — an ~8B single-stream Diffusion Transformer (DiT), Apache-2.0, released April 2026, repackaged for ComfyUI by Comfy-Org. It is not an instruction-based image editor.
- ERNIE-Image (base): ~50 steps for peak quality.
- ERNIE-Image-Turbo: distilled (Distribution Matching Distillation + RL), high-fidelity in ~8 steps, cfg 1. The downloaded pack uses Turbo (
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 = best open-weight text rendering + layout T2I. Qwen-Image-Edit = instruction editing. Flux Kontext = reference editing. Z-Image Turbo = fast general T2I (and this same pack pairs the two — see Combo pipelines).
Separated packs (render-verified)
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 — avoids a filename clash).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 238 lines · 98 tokens per session scan A 3cf4e7311556
ernie-image is a skill published in the GitHub repository sandyup/comfyui-mcp (2 stars, last pushed 3mo ago), licensed MIT. It adds 98 tokens to every session and 5,435 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to ernie-image, differing in 104 lines, and is treated as a copy.
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