ComfyUI-Spectrum-sdxl
ComfyUI-Spectrum-SDXL is a custom node for ComfyUI that implements the Spectrum diffusion acceleration technique
Paketprofil
- Status
- Überprüft
- Verleger
- @ruwwww
- Quelle
- GitHub
README
ComfyUI Spectrum SDXL Node
This repository contains a Unnoficial ComfyUI custom node implementing the Spectrum sampling acceleration technique, tailored specifically for SDXL models. Spectrum is a training-free method that forecasts spectral features using Chebyshev polynomials and ridge regression to skip redundant UNet computations, achieving significant speed-ups with less quality loss.
Disclaimer: This implementation follows the official Spectrum paper logic but caches the outer feature rather than the inner feature approach.
Legacy / Non-Faithful Node: The
SpectrumSDXLCalibratednode is now considered legacy.Clarification for returning users: The previous version of this node was essentially "vibe-coded" from scratch because I couldn't initially find the official forecaster implementation. This led to some non-principled additions like "calibration" which, while interesting, are not faithful to the paper. This has now been solved by porting the official forecaster code into the
SpectrumSDXLnode. Please migrate to the faithful implementation for more stable and principled results.Performance comparison — Download the images below and drag them into ComfyUI to instantly load optimized workflows!
SDXL Calibrated Comparisons (30-step Euler)
Normal Spectrum Calibrated (strength 0.5) Calibrated (strength 0.8) Normal Spectrum Cal0.5 Cal0.8 8.8 s 4.8 s 4.8 s 4.8 s Normal2 Spectrum2 Cal0.5_2 Cal0.8_2 8.3 s 4.6 s 4.6 s 4.6 s Anima (30-step er-sde)
Default Spectrum Default Anima Spectrum Anima 23.67 s 13.01 s
Key Features
- Sampling Acceleration – Reduce inference time (up to ~2× on SDXL) by skipping UNet evaluations on selected timesteps.
- Vectorized Batch Processing – Fully vectorized mathematical operations process conditional and unconditional latents independently. This prevents memory contamination (rainbow artifacts) and sustains ultra-high
it/sspeeds without Python loop bottlenecks. - FP8 Tensor-Core Support – Compatible to run on NVIDIA Tensor Cores in FP8 mode, providing additional speed gains on compatible hardware. Works seamlessly alongside other optimizations.
- Sage-Attention Friendly – Orthogonal to Sage Attention; you can enable them together without conflicts.
- Stability Enhancements – Incorporates a "Sliding Window" memory limit (prevents mathematical explosions), alongside jitter and anti-NaN safeguards to keep low-precision runs (FP16/FP8) perfectly stable.
- Step-Based Quality Guard – A dedicated parameter allows you to seamlessly turn off the forecaster during the final critical steps, preserving high-frequency micro-details (like skin texture and eyes) and eliminating VAE-like compression blur.
Installation
- Navigate to the
custom_nodesdirectory of your ComfyUI installation. - Clone this repository:
git clone https://github.com/ruwwww/comfyui-spectrum-sdxl
- Restart ComfyUI.
Parameters
| Parameter | Description
Knoten in diesem Paket
3 Knoten (Plural)
Knoten in diesem Paket
3 Knoten (Plural)- CalibratedSpectrumSDXL
- SpectrumSDXL
- SpectrumSDXLCalibrated
Verwandte Ressourcen
3 Verbindungen
Verwandte Ressourcen
3 VerbindungenQuellen
3 Quellen
Quellen
3 QuellenVerifiziert 1. Okt.
Verifiziert 1. Okt.
Quellenauszüge
1 Auszug
Quellenauszüge
1 AuszugSource context: Repo ruwwww/ComfyUI-Spectrum-sdxl
