How I Actually Choose AI Models for Motion Graphics

I was losing too many hours swapping between models for the same type of shot. One would nail the style but ruin the text. Another gave perfect numbers but looked dead. This repo is what I wish I had when I started testing for real commercial projects.

The problem with "just use this model" advice

Every tutorial picks a winner. In practice the winner changes with the job. A bar chart for a product explainer is nothing like a typography sequence for a luxury brand.

I tested on actual briefs: Vox-style explainers, Tanishq-style jewellery campaigns, Horlicks fitness content, and retro product ads. The repo has the full decision tree, locked style sheets, and complete prompt sets from those tests.

Quick decision tree I now use

Need exact data or charts with real numbers? Use Remotion. It is code, so the numbers never lie and you can generate a thousand variants without extra cost.

Need dynamic camera moves, reference images, or readable typography? Omni Flash wins most of the time. It understands style sheets better than anything else I tried.

Pure cinematic beauty with almost no text? SeaArt 2 still looks the best for mood and light.

On a tight budget and mostly social content? Omni Flash is the cheapest of the strong options.

For real client work I almost always do hybrid. Omni for the moving shots and style, Remotion for anything with data or lower thirds, then After Effects for the final polish and sound.

What the tests actually showed

Omni Flash is the one I reach for first now. The reference image system is strong enough that I can lock a style once and mostly stay consistent across a sequence. Typography is usable on 80-90% of shots if the fonts are big and clean. Small text still needs workarounds.

Remotion is the safety net. When the client cares about the exact percentage or the date on screen, I do not gamble with diffusion. I build it in code.

SeaArt surprised me on pure visuals but fell apart the moment text or logos entered the frame.

Kling and some of the others are still too unreliable for anything with brand guidelines.

The repo has side-by-side notes and the actual style blocks I locked for each test.

The workflow that survived real deadlines

I start with one locked style reference sheet. Colors, fonts, key elements, and mood all written out in plain text. Then I generate one strong reference image from that sheet.

For each clip I keep the style block identical and only change the action block. That single rule removed most of the drift.

For logos and known faces I generate the element first as a still, then bring it into the video pass. Trying to do everything in one image-to-video call almost always breaks something.

All the working prompts and the full 60-second explainer example are in the repo.

What this actually saves for client work

I stop guessing which model will behave on a given shot. The decision tree means I pick faster and the first or second generation is usually close enough to ship after light fixes.

The hybrid approach is not theory. It is what let me deliver the kind of work that used to take a full motion team.

If you are spending the same hours I was, the repo is here: https://github.com/madebysaira/ai-motion-graphics-comparison

It includes the style sheets, the full prompt templates, and the exact decision points that came out of shipping the work instead of just testing it.

If this kind of practical breakdown is useful for your own projects, book a quick call and tell me what you are trying to make.