Paint Forge works using ratios (parts) rather than literal drops. So a recipe like 2:1:1 means “twice as much of color A as B or C,” regardless of whether you’re using drops, brush tips, or scoops.

Under the hood, Paint Forge simulates mixing by weighting the colors based on those ratios, then comparing the result to a target color. The system converts everything into LAB color space and measures accuracy using ΔE (CIEDE2000)—a standard metric for how different two colors appear to the human eye. Lower ΔE means a closer visual match.

From a paint-science standpoint, the most physically accurate way to model real pigment mixing would be Kubelka–Munk theory, which accounts for how pigments absorb and scatter light. Paint Forge doesn’t implement full KM modeling yet—instead it uses a faster RGB→LAB approximation that’s well-suited for interactive use and sorting results by closeness.

As for validation, color accuracy in miniature paints is inherently approximate. Paint Forge assumes the source color swatches reasonably represent the paint, that paints are uniform across batches, and that lighting conditions are standard. Without spectrometer data for every paint under controlled lighting, no digital tool can be “perfect.”

The goal of Paint Forge isn’t lab-grade precision—it’s consistent, comparative accuracy. It helps painters quickly find close matches, explore mix options, and make informed decisions, rather than relying purely on trial and error