Wiring & Fixing Apply ControlNet (Advanced)
Practical pin-by-pin connection order and common error fixes for Apply ControlNet (Advanced) in ComfyUI workflows.
Updated Oct 17, 2026 · 1 min read
- Target Node
- Apply ControlNet (Advanced)
- Required Inputs
- positive, negative, control_net, image, strength, start_percent, end_percent
- Output Pins
- positive (CONDITIONING), negative (CONDITIONING)
- Package
- Built-in Core
Step-by-step pin wiring for Apply ControlNet (Advanced)
- Drop Apply ControlNet (Advanced) onto the canvas by double-clicking and searching its title.
- Connect all required upstream wires (`positive, negative, control_net, image, strength, start_percent, end_percent`) from your checkpoint loader, prompt conditioning, or image preprocessor.
- Route the output (`positive (CONDITIONING), negative (CONDITIONING)`) into your downstream KSampler or VAE Decode node, then click **Queue Prompt**.
Fixing dependency conflicts and type mismatches
If the console prints a Python import error or tensor shape mismatch on this node, verify that your checkpoint family (SD 1.5, SDXL, or Flux) matches any attached LoRA, ControlNet, or IPAdapter weight.
For custom node packs on Windows, run **Update All** inside ComfyUI-Manager or grab a fresh desktop environment from /download.
FAQs
Why won't a wire snap onto Apply ControlNet (Advanced)?
ComfyUI enforces strict pin types. Check that the upstream output matches `positive, negative, control_net, image, strength, start_percent, end_percent` and insert a VAE Encode/Decode or preprocessor node if converting between pixels and latents.
How do I bypass this node temporarily without deleting my wires?
Select the node on the canvas and press **Ctrl+B** (Bypass) or **Ctrl+M** (Mute) to test your graph without disconnecting cables.
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