3 Models Available
A creator builds an AI persona once on Nano Banana 2, then uses Flux Kontext for outfit and scene swaps without losing the face. On Martini's canvas, anchor a canonical reference portrait, then fan out to Nano Banana 2 (face-locker), Flux Kontext (outfit/scene edits while preserving identity), and Runway Gen4 Image nodes for situational variants. Output is a 12-pose AI influencer character sheet: front/three-quarter/profile portrait, plus wardrobe and location swaps generated from the same anchor. Pick a model below to walk through the canonical-reference workflow your character series depends on.
Build an AI persona once on Nano Banana 2 and ship a character sheet that holds across pose, outfit, and scene shifts on the Martini canvas. Nano Banana 2 is the strongest face-locker in the stack: it accepts up to 10 reference images and outputs at 1K, 2K, or 4K, with face consistency that survives 50+ generations from the same canonical reference. For AI influencer producers who keep one persona identical across a 12-week content series, this is the load-bearing model — every other model in the chain inherits the lock from here.
Black Forest Labs
Edit your locked character into new outfits, scenes, and poses on Martini using FLUX Kontext — built specifically for instructed image edits that preserve subject identity. Where Nano Banana 2 generates the canonical character sheet, FLUX Kontext is the wardrobe-and-scene editor that takes that locked still and modifies it without losing the face. The two-model chain (Nano Banana 2 to lock identity, FLUX Kontext to vary wardrobe) is the cleanest character-consistency pipeline on the canvas.
Vidu
Generate consistent character stills on Martini using Vidu Reference-to-Image — accepts 1-7 reference images per generation and outputs character stills that flow directly into Vidu video nodes for matched motion. Vidu's reference workflow is optimized for the image-to-video character pipeline: the same model family that locks identity on the still also handles the motion, eliminating cross-model identity drift at the modality boundary. For producers who plan to ship character video content downstream, Vidu Reference-to-Image is the cleanest single-vendor path.