OpenArt.ai Review: Multi-Model AI Creative Hub, Tested
OpenArt is a multi-model creative hub: rather than shipping one house AI model, it gives you a single account and interface across a wide range of image and video engines — currently including Seedance 2.0/2.5, Kling 3.0, Sora 2, Google Veo 3, MiniMax Hailuo, and HappyHorse for video, and GPT Image 2, Nano Banana Pro, Seedream 5.0, Grok Imagine, and Qwen Image 3 for images. That lineup shifts as providers release new versions, so treat any specific model list — including this one — as a snapshot, not a permanent fact. I ran the same product-ad brief through three of the video models side by side — the exact kind of comparison OpenArt is built to make easy — to see whether switching models inside one interface actually saves the time it promises, or just moves the friction somewhere else. What you can actually do with it Image generation across multiple diffusion and transformer-based models, with text-to-image and image-to-image workflows. Video generation up to 15 seconds at 4K, using whichever underlying model you select. Editing tools — inpainting, background removal/swap, and upscaling to 4K. Character Builder — trains a consistent character you can reuse across multiple generations, useful for series content or a recurring brand mascot.
One Man vs Assassins: Seedance 2.0 First-and-Last-Frame Prompt
This one's a first-and-last-frame generation, not a straight text-to-video prompt — a different technique worth knowing if you're experimenting with Seedance 2.0. Instead of describing the whole scene from scratch, you give the model two reference frames (how the fight starts, how it ends) and let it fill in the motion between them. A frame from my video for this article (tap to watch) That constraint is what makes the result feel choreographed instead of random: the model has to invent a path from point A to point B, which is exactly how a real fight-scene storyboard works. Asking for "different perspectives" on top of that pushes it to cut between angles the way an actual action sequence would, instead of holding one static shot. This first-and-last-frame approach is worth knowing beyond fight choreography, too — it works for any shot where you care more about the beginning and end state than the exact path between them: a product transforming, a room being built or destroyed, a time-lapse-style change. A full text-to-video prompt has to describe motion in words, which is hard to get precise; handing the model two frames sidesteps that problem entirely and lets the interpolation do the work language struggles
