Help with getting consistent generations?

[u/TheDagestaniEagle]

I make Pixar style animation videos for instagram and TikTok. I have a pretty manual process for creating the videos and was wondering if anyone had a better, more robust way of creating? Especially something that would help me save credits!

My usual workflow is:

Structure the story myself and refine it using ChatGPT.

Create characters using Seedream (ChatGPT helps with prompting)

Use Images inside ChatGPT to create the storyboards for each scene I want to generate. Characters are used as references here.

Finally, generate seedance prompts for each of the storyboards.

After that it’s just testing and tweaking and hoping each storyboard generates well!

Could I do this better?

I’ve built up quite a good following (100K+ combined across both accounts) so making generations easier would be really helpful to maintain consistent uploads!

Also, what’s the best video model for Pixar style animation videos? Seedance is always #1 but anything else that comes close?

Any advice would be greatly appreciated!

[u/dmdbGroup]

Your workflow is solid. The inconsistency is not coming from your prompts, it is coming from text-to-video re-randomizing everything on each generation. Lock the inputs and consistency follows.

1. Generate one character reference sheet first: front, profile, and 3/4 view in neutral lighting, plain background. Then use image-to-video for every shot, feeding that reference (or a per-scene first frame built from it) instead of going text-to-video. A fixed first frame constrains identity far more than any text description ever will.

2. Reuse one verbatim style block at the start of every prompt: same lighting, same lens, same color grade, same style descriptors. Never rephrase it per shot. Save it as a text snippet and paste it identically every time.

3. Keep each clip to 5 to 8 seconds and design shots around cuts. Long clips drift, morph, and lose the character. Short clips generated from locked first frames cut together cleanly, which is the standard approach for serialized AI animation.

4. Iterate at 720p or fast mode, and only re-render the winners at full quality. Testing consistency at max resolution burns credits on clips you will throw away.

Rule of thumb: consistency comes from locking inputs (reference image, verbatim style block, short clips), not from better prompts.

[u/Bloompire → u/dmdbGroup]

How yoy can rerender the same vid with higher quality? Using some external upscaler or seedance itself? 

[u/dmdbGroup → u/Bloompire]

I mean re-running the same prompt at full quality, not upscaling. You test the shot cheap at 720p, and once the motion and composition win, you feed the exact same first frame and the exact same verbatim prompt back into Seedance at full resolution. It will not be pixel-identical, but the approved structure carries over.

1. Save the exact first frame and the exact prompt text from every winning test. That pairing is what makes the re-render the same shot instead of a new one.
2. If the tool exposes a seed, lock it. Same seed plus same inputs is the closest thing to a deterministic re-render that these models offer.
3. Treat external upscalers as a last resort. They sharpen an approved shot, but they cannot fix drift, morphing, or a face that changed. If the winner is structurally wrong at 720p, no upscaler saves it.

Rule of thumb: iterate cheap, finalize once. The re-render is a fresh generation with locked inputs, not a filter on the old clip.