How ComfyUI prompts work
- Positive and negative prompts are separate CLIP Text Encode nodes wired into the sampler — there’s no single prompt box.
- Plain (token) applies 1.1× emphasis; nested parentheses and explicit (token:1.2) weights also work. The standard parser does not apply A1111’s [token] de-emphasis.
- LoRAs load via a Load LoRA node (separate model and CLIP strength), not inline <lora:…> text.
- Use Conditioning (Concat) nodes to isolate concepts — the equivalent of A1111’s BREAK.
Example ComfyUI prompt
masterpiece, best quality, a lighthouse on a storm-lashed cliff, dramatic clouds, (volumetric light:1.2), cinematic, ultra-detailed
negative: worst quality, low quality, blurry, deformed
Build ComfyUI prompts faster with Prompt Builder
- Compose the positive and negative prompts with reusable snippets, then paste into your CLIP Text Encode nodes.
- Drag in a ComfyUI PNG to recover its embedded prompts — no node spelunking.
- One-key (token:1.2) weighting without counting parentheses.
- Save and share full prompt recipes with the community.
Frequently asked questions
How are ComfyUI prompts different from Automatic1111?▾
Both support plain (token) emphasis at 1.1× and numeric weights. ComfyUI uses separate prompt and LoRA nodes; its standard parser does not apply A1111’s [token] de-emphasis.
Can I import a prompt from a ComfyUI image?▾
Yes — drag the PNG into Prompt Builder and it reads the embedded ComfyUI workflow metadata to recover the prompts.
Does (token:1.2) weighting work in ComfyUI?▾
Yes, the numeric form works. Use a Load LoRA node for LoRAs rather than inline <lora:…> text.