Quantize
Reduces the image to N total colors using k-means clustering for whole-image palette reduction.
Quantize reduces the entire image to a specified number of unique colors. It uses k-means to find the best representative colors, then remaps every pixel to its nearest match. This creates a flat, stylized look similar to indexed-color images.
Unlike Posterize (which operates per-channel), Quantize considers the full RGB color together, producing a more harmonious and intentional palette.
Connect the optional Palette input to snap each pixel to the nearest color in a wired palette using a perceptual match, the same way Dither does. With no palette connected, the k-means behavior is unchanged and the color count controls the result.
Parameters
Section titled “Parameters”Pins
Color
Number of unique colors in the output (k-means clustering)
K-means restart attempts; higher = better but slower
Apply Bayer 4x4 dithering to reduce banding
Auto-enabled when a Palette is connected (drives the color set)
Usage Tips
Section titled “Usage Tips”- Enable dithering to reduce visible banding and color transitions.
- Use 8–16 colors for a retro/pixel art style.
- Connect a Palette (from a Palette, Palette From Image, or Palette From Gradient node) to remap to an exact set of colors instead of letting k-means pick them.
- For a dithered version of the same palette snap, use the Dither node, which spreads quantization error for smoother gradients.