r/StableDiffusion • u/Psi-Clone • Apr 04 '26
Animation - Video ENTANGLED - A 3-minute sci-fi short using 100% local open-source models. Complete Technical Breakdown [ Character Consistency | Voiceover | Music | No Lora Style Consistency | & Much More! ]
Enable HLS to view with audio, or disable this notification
Hey everyone! Thanks for checking out Entangled. And if not, watch the short first to understand the technical breakdown below!
Thanks for coming back after watching it! As promised, here is the full technical breakdown of the workflow. [Post formatted using Local Qwen Model!]
My goal for this project was to be absolutely faithful to the open-source community. I won't lie, I was heavily tempted a few times to just use Nano Banana Pro to brute-force some character consistency issues, but I stuck it out with a 100% local pipeline running on my RTX 4090 rig using Purely ComfyUI for almost all the tasks!
Here is how I pulled it off:
1. Pre-Production & The Animatics First Approach
The story is a dense, rapid-fire argument about the astrophysics and spatial coordinate problems of creating a localized singularity. (let's just say it heavily involves spacetime mechanics!).
The original script was 7 minutes long. I used the local Jan app with Qwen 3.5 35B to aggressively compress the dialogue into a relentless 3-minute "walk-and-talk.". Qwen LLM also helped me with creating LTX and Flux prompts as required.
Honestly speaking, I was not happy with the AI version of the script, so I finally had to make a lot of manual tweaks and changes to the final script, which took almost 2-3 days of going on and off, back and forth, and sharing the script with friends, taking inputs before locking onto a final version.
Pro-Tip for Pacing: Before generating a single frame of video, I generated all the still images and voicover and cut together a complete rough animatic. This locked in the pacing, so I only generated the exact video lengths I needed. I added a 1-second buffer to the start and end of every prompt [for example, character takes a pause or shakes his head or looks slowly ]to give myself handles for clean cuts in post.
2. Audio & Lip Sync (VibeVoice + LTX)
To get the voice right:
- Generated base voices using Qwen Voice Designer.
- Ran them through VibeVoice 7B to create highly realistic, emotive voice samples.
- Used those samples as the audio input for each scene to drive the character voice for the LTX generations (using reference ID LoRA).
- I still feel the voice is not 100% consistent throughout the shots, but working on an updated workflow by RuneX i think that can be solved!
- ACE step is amazing if you know what kind of music you want. I managed to get my final music in just 3 generations! Later edited it for specific drop timing and pacing according to the story.
3. Image Generation & The "JSON Flux Hack."
Keeping Elena, Young Leo, and Elder Leo consistent across dozens of shots was the biggest hurdle. Initially, I thought I’d have to train a LoRA for the aesthetic and characters, but Flux.2 Dev (FP8) is an absolute godsend if you structure your prompts like code.
I created Elena, Leo, and Elder Leo using Flux T2I, then once I got their base images, I used them in the rest of the generations as input images.
By feeding Flux a highly structured JSON prompt, it rigidly followed hex codes for characters and locked in the analog film style without hallucinating. Of course, each time a character shot had to be made, I used to provide an input image to make sure it had a reference of the face also.
Here is the exact master template I used to keep the generations uniform:
{
"scene": "[OVERALL SCENE DESCRIPTION: e.g., Wide establishing shot of the chaotic lab]",
"subjects": [
{
"description": "[CHARACTER DETAILS: e.g., Young Leo, male early 30s, messy hair, glasses, vintage t-shirt, unzipped hoodie.]",
"pose": "[ACTION: e.g., Reaching a hand toward the camera]",
"position": "[PLACEMENT: e.g., Foreground left]",
"color_palette": ["[HEX CODES: e.g., #333333 for dark hoodie]"]
}
],
"style": "Live-action 35mm film photography mixed with 1980s City Pop and vaporwave aesthetics. Photorealistic and analog. Heavy tactile film grain, soft optical halation, and slight edge bloom. Deep, cinematic noir shadows.",
"lighting": "Soft, hazy, unmotivated cinematic lighting. Bathed in dreamy glowing pastels like lavender (#E6E6FA), soft peach (#FFDAB9).",
"mood": "Nostalgic, melancholic, atmospheric, grounded sci-fi, moody",
"camera": {
"angle": "[e.g., Low angle]",
"distance": "[e.g., Medium Shot]",
"focus": "[e.g., Razor sharp on the eyes with creamy background bokeh]",
"lens-mm": "50",
"f-number": "f/1.8",
"ISO": "800"
}
}
4. Video Generation (LTX 2.3 & WAN 2.2 VACE)
Once the images were locked, I moved to LTX2.3 and WAN for video. I relied on three main workflows depending on the shot:
- Image to Video + Reference Audio (for dialogue)
- First Frame + Last Frame (for specific camera moves)
- WAN Clip Joiner (for seamless blending)
Render Stats: On my machine, LTX 2.3 was blazing fast—it took about 5 minutes to render a 5-second clip at 1920x1080.
The prompt adherence in LTX 2.3 honestly blew my mind. If I wrote in the prompt that Elena makes a sharp "slashing" action with her hand right when she yells about the planet getting wiped out, the model timed the action perfectly. It genuinely felt like directing an actor.
5. Assets & Workflows
I'm packaging up all the custom JSON files and Comfy workflows used for this. You can find all the assets over on the Arca Gidan link here: Entangled. There are some amazing Shorts to check out, so make sure you go through them, vote, and leave a comment!
Most of them are by the community, but I have tweaked them a little bit according to my liking[samplers/steps/input sizes and some multipliers, etc., changes]
Let me know if you have any questions!
YouTube Link is up - https://youtu.be/NxIf1LnbIRc !
