How AI logo generators actually work under the hood
A non-handwavy explanation of diffusion, vector models, and why your prompt matters more than the model you pick.
Most 'AI logo generators' on the market are templating engines with a thin layer of GPT polish. Real generative pipelines look like this:
01 · The brand strategist
We pass your sentence to Claude Sonnet 4.5. It returns structured JSON: visual brief, recommended model, palette, type pairing, four distinct visual directions. This is the most important step. Better briefs make better logos.
02 · The right model for the job
Recraft v3 returns native SVG and excels at vector logos. Ideogram v3 renders accurate text — critical for wordmarks. FLUX schnell is fast and creative for art-directed marks. We route per-variation, not per-brand.
03 · Diffusion, briefly
All three image models are diffusion models: they start from random noise and denoise step-by-step toward your prompt. Recraft adds a vector head that emits SVG paths instead of pixels. Ideogram adds a text-rendering loss so 'Halogen' actually reads as Halogen.
04 · Mockups via image-to-image
For mockups (your logo on a t-shirt, a coffee cup, a storefront) we route everything through Nano Banana's edit endpoint, with the source logo passed as a reference image and a photoreal prompt. The model preserves the logo and re-renders the surrounding scene.
05 · What the prompt should contain
Era reference, mood, iconography, composition. Avoid generic adjectives like "modern" or "clean" — every prompt has them. Be specific: "1970s industrial, tungsten filaments, apothecary charm, Braun-era Dieter Rams sensibility." That sentence is worth a hundred adjectives.