My company (Nim) is hosting Hunyuan model, so here's a quick test (first attempt) at "pelican riding a bycicle" via Hunyuan on Nim: https://nim.video/explore/OGs4EM3MIpW8
I think it's as good, if not better than Sora / Veo
My company (Nim) is hosting Hunyuan model, so here's a quick test (first attempt) at "pelican riding a bycicle" via Hunyuan on Nim: https://nim.video/explore/OGs4EM3MIpW8
I think it's as good, if not better than Sora / Veo
What does it produce for “A pelican riding a bicycle along a coastal path overlooking a harbor”?
Or, what do Sora and Veo produce for your verbose prompt?
The Pelican is doing some weird flying motion, motion blur is hiding a lack of detail, cycle is moving fast so background is blurred etc. I would even say SORA is better because I like the slow-motion and detail but it did do something very non physical.
Veo is clearly the best in this example. It has high detail but also feels the most physically grounded among the examples.
If you'd like to replicate, the sign-up process was very easy and I was easily able to run a single generation attempt. Maybe later when I want to generate video I'll use prompt enhancement. Without it, the video appears to have lost a notion of direction. Most image-generation models I'm aware of do prompt-enhancement. I've seen it on Grok+Flow/Aurora and ChatGPT+DallE.
Prompt
A pelican riding a bicycle along a coastal path overlooking a harbor
Seed
15185546
Resolution
720×480Turning content blockers off does not make a difference.
Then there's Lightricks LTX-1 model and Genmo's Mochi-1. Even the research CogVideoX is making progress.
Open source video AI is just getting started, but it's off to a strong start.