How do you compare AI image models to choose the best one for a character before video production?
Last updated June 26, 2026
Compare AI image models by running the identical character prompt on candidate models in parallel — Recraft, Nano Banana Pro, GPT-Image-2 — then judging outputs on skin realism, prompt adherence, and identity hold across angles before locking one. One documented production ran two models simultaneously through a casting agent and locked each character in about 5 generations at ~$9.78 per character.
Treat model comparison as a casting audition: the same character brief goes to every candidate model at the same time, and you judge the results side by side instead of testing models one after another. invideo is an agentic video creation tool with all the current image and video models available, so you can run the whole comparison in one place and let the invideo agent route the same prompt to each model.
| Model | Skin realism | Prompt adherence | Best use for character work |
|---|---|---|---|
| Recraft | Strong — pores, lines, stubble; faces read photoreal | Solid | Hero portraits where the face has to feel like a castable actor |
| Nano Banana Pro | Can feel stock-photo-y | Very high | Multi-angle character sheets and turnarounds; outperforms Nano Banana 2 for character work |
| GPT-Image-2 | Balanced, clean anatomy | High | Stylized or graphic-leaning character looks; a strong third option to audition |
Across documented tests, no single model wins on every axis — which is exactly why you audition them in parallel on YOUR character before locking one.
1. Run the same prompt on multiple models in parallel. Set up a casting agent, give it your character description, and instruct it to run the identical prompt on two or more image models simultaneously rather than sequentially — parallel runs are what compress casting iteration. A documented 3-day production used exactly this protocol: one casting agent, two image models, same prompt, side-by-side results.
2. Judge on specific criteria, not general quality. Recraft generates facial portraits with skin-level imperfections that make a face read as photoreal rather than rendered — "ReCraft actually gives you those imperfections like pores, lines, stubble, like all the little stuff that makes a face look like an actual face," as Hridaye, invideo's creative director, put it. Nano Banana Pro has very strong prompt adherence, but in the same documented test its outputs felt "extremely stock photo-y" to the director — a real trade-off to weigh against your film's look, and Nano Banana Pro still outperforms Nano Banana 2 for character work. Include GPT-Image-2 in the lineup and apply the same tests to it: anatomical believability, adherence to the brief, and whether the face feels like a castable actor rather than a stock asset.
3. Generate options per model, not single images. Generate several variations of the character from each candidate and pick the strongest. One production generated 4 options per character sheet, selected the best, and locked it before any video generation began. Image generation is cheap relative to video credits, so optionality at this stage costs little and saves regeneration later.
4. Stress-test the winner with a multi-angle character sheet. Have the leading model produce a turnaround sheet — multiple angles plus face and mid-distance closeups at the highest available resolution — and check that identity holds across every panel. Include close-up panels for small details like scars and accessories, and remove objects from the character's hands before generating the turnaround so they don't introduce inconsistency across angles. A model that nails one hero portrait but drifts across angles loses the audition.
5. Lock the winner before any video generation. Locking character sheets up front is what prevents consistency problems through the rest of the film — no LoRA fine-tuning required, even though most guides treat fine-tuning as the only reliable route.
Watch some of these to see what works for you:
ReCraft actually gives you those imperfections like pores, lines, stubble, like all the little stuff that makes a face look like an actual face.
— Hridaye, invideo's creative director