ComfyUI-ModelSamplingSD3Advanced

A ComfyUI node that adds windowed, curved “shift” control for Flow Matching samplers (SD3-style / flow schedules). It is a drop-in replacement for Comfy's included ModelSamplingSD3 node.

This was built specifically for Flow Match models such as bigASP, where I have observed:

• Better prompt adherence at higher shift (especially early in denoising),
• but worse image quality / texture / coherence if that high shift persists into later steps.
• Especially when using character LoRAs.

ModelSamplingSD3Advanced lets you apply a high shift in early steps (to lock in prompt adherence), then transition to a lower shift later (to maintain quality.)

---

What this node does

The node patches the model’s model_sampling with a custom flow schedule where shift varies over denoise progress:

• shift_start used near the beginning (high noise / early steps)
• shift_end used later (low noise / late steps)
• a window (start_percent → end_percent) defines where the transition occurs
• a curve controls how that transition feels (linear, cosine, smoothstep, etc.)

---

Installation

You can clone this repo into comfyui/custom_nodes/ComfyUI-ModelSamplingSD3Advanced or search for "Model Sampling SD3 Advanced" in the ComfyUI Manager.

---

Inputs

• model: The incoming model.
• shift_start: Shift value at the beginning (early/high-noise steps).
• shift_end: Shift value at the end (late/low-noise steps).
• start_percent: Denoise progress where the transition window begins.
• end_percent: Denoise progress where the transition window ends.
• curve: Shape of the transition inside the window:
  • linear, cosine, smoothstep, ease_in, ease_out, sigmoid
• outside_window: Controls behavior outside the window:
  • hold (default): before start_percent uses shift_start, after end_percent uses shift_end
  • baseline: outside the window uses the model’s default shift (strictly windowed modulation)
  • linear_extrapolate: extends the shift trend beyond the window (advanced)
• multiplier: Flow schedule timestep multiplier (typically 1000). Keep default unless you know why you’re changing it.

Output

• MODEL: A patched model with the modified sampling schedule.

---

Notes / Caveats

• This node modifies the sampling schedule; results can be model-specific.
• The node is meant for Flow Matching / SD3-style schedules (not classic epsilon/DDIM schedules).
• If your workflow/sampler expects strictly monotonic sigmas, this implementation enforces monotonicity as a safety measure.