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After hundreds of text-to-CAD prompts, patterns emerge. Specific dimensions beat vague descriptions. Simple geometry beats ambitious complexity. Here are the prompts that actually work.
Three tools, three different approaches to AI-assisted CAD. Zoo generates geometry. AdamCAD gives you parametric sliders. CADGPT writes scripts. They're not really competing.
Zoo.dev is the closest thing to a real text-to-CAD tool right now. It generates actual STEP files from text prompts using its own geometric kernel. It's also not magic.
People keep mixing these up. Text-to-CAD generates geometry from words. Generative design optimizes geometry under constraints. They solve different problems and they're not interchangeable.
A side-by-side comparison of every text-to-CAD tool I could get my hands on in 2026. Spoiler: the field is thin and the results are uneven.
I measured text-to-CAD output with calipers (after printing) and compared it to what I asked for. The answer is: sometimes close, sometimes not, and never with the confidence you'd want for production.
Text-to-CAD tools can generate simple parts. They cannot handle assemblies, tolerances, complex surfaces, or anything that requires actual engineering judgment. Here's the full list of what breaks.
CADScribe tries to generate CAD models from text descriptions. Sometimes it works. Sometimes it hands you geometry that looks like it gave up halfway through.
CADGPT writes AutoLISP and Python scripts for CAD automation. It does not generate 3D models. If you know what it actually is, it's occasionally useful.
I ran the same prompts through every text-to-CAD tool I could find. Most of them produced geometry that looked like a dare. A few produced real parts.
