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The original was posted on /r/stablediffusion by /u/Darqsat on 2026-08-19 17:06:52+00:00.

I spent last 6 hours trying various prompts for reference model to better understand how it works, and what this model can do. As a base guide I used Minimax H3 ref guide.

My goal was to find a working prompt to use Minimax similar to how SCAIL works, when you can edit a video and replace a character on a video with your referenced character. I didn’t want to transfer movement and only wanted to REPLACE character completely.

I would like to post my best working prompt and let you test it, and share your experience or share a better prompt.

subject_definitions:
<Subject 1> is woman in <Picture 1> with redhead and black tank top.
<Subject 2> is the woman originally in <Video 1>.

summary:
[video editing + Audio reuse] The target video is an edited version of <Video 1>. <Subject 2> is replaced with <Subject 1>, who takes over her pose and movement.

retention_analysis:
<Subject 1> (appears in [Shot 1]): fully_preserved - her face, hairstyle, and body from <Picture 1> are retained throughout. Her clothes are not retained.
<Subject 2> (appears in [Shot 1]): attribute_transfer - her pose, movement, and screen position are transferred to <Subject 1>.

detailed_description:
The target video keeps <Video 1>'s original style, lighting, and camera work unchanged.

overall_soundscape: N/A
non_diegetic_music: N/A

What are my discoveries:

  • You don’t need to describe action in detailed_description. I did it for first 100 attempts, and then dropped it and it seems like not influencing an output.
  • It can often detect your Subject with simple description, but in complex scenes it needs better anchoring to not mess up those characters. Most of my input image was a woman in medium shot, so just describing it as “woman” was enough, but 50/50 generations keep losing identity so you have to add better and stronger anchor for model - something visually big like hair, clothing, position on screen. Works both ways for reference video and for reference image. The stronger you describe <Subject N> the more stable the reference.
  • The least successful edits were those where a character on video is barely recognizable. I have couple videos where a character is close to camera and only part of face is visible in active movement, such videos are my biggest unsuccess.
  • Summary section seems like has the most its anchor to pre-trained keywords which can be found in their prompting guide. [video editing] is a keyword which tells a model that it must go frame by frame and EDIT something. I was testing other things and in given prompt you will see some info about character replacement, but I don’t see that it really influences anything.
  • Retention analysis section seems like the next MAIN or even only main driver for a work description for a model. And most of successful edits was build with properly used triger words like fully_preserved, attribute_transfer. You can find those keywords in linked guide. Still not sure about (appears in [Shot 1]), I doubt it has influence on a prompt, but its by far best prompt so I keep it.
  • [audio reuse] trigger in summary works, but it seems that model rewrite its, so I can tell its same audio but remade by model, and if model has weak concept of a sound it does it poorly. Maybe I need to pay more attention to prompting guide and describe audio better in retention section.

I’ve generated more than 400 videos while testing and gaining knowledge, and I think I have good progress. So I am curious to see if anyone else can help me with this journey and together we can crack the model and find a proper working prompt or other ideas.

The playground was pruned_int8_convrot model, with turbo lora from lightX with 4 steps, and I tested most of them on 5 sec duration. I did tests on 15s and it worked fine, but I kept 5s to keep gen time lower and just train prompting.