Back when AI video generation was still in its infancy, Stable Video Diffusion was one of the earliest models in the market.
Fast forward to 2025, and it is still relatively competitive, even amongst new, fierce rivals like Runway, Kling AI, and Sora.
Here, I’ve put together a detailed review that explores its strengths, weaknesses, and whether it still holds up against the latest generation of AI video tools.
Stable Video Diffusion: A Detailed Overview
Launched on November 21, 2023, by Stability AI, Stable Video Diffusion (SVD) is a foundation AI video generation model. It is also one of the first open-source AI video models in the market that allows users to generate all kinds of dynamic videos via descriptive text prompts or by uploading reference images.
In terms of image-to-video generation, Stability AI created two main models: SVD and SVD-XT. The SVD model can generate 14 frames of motion at 576×1024 resolution, whereas SVD-XT employs a similar framework but extends it up to 24 frames.
I should also point out that Stability AI launched other AI models like Stable Video 3D, and Stable Video 4D, which is their first video-to-video generator.
While it’s no secret the developer has undergone a shaky period, it seems to be recovering. In fact, it managed to raise $80 million in funding last year and even recruited film director James Cameron to join their board.
What Was My Experience Using Stable Video Diffusion?
I tested Stable Video Diffusion using different visual styles like animation, 3D, surrealism, and more. Here’s what I discovered:
For one, I was fairly impressed by how it keeps the various image backgrounds looking very realistic. However, sometimes the animation of characters could feel a bit stiff or unnatural during slow movement, just like the example below.
| Prompt | Generated video |
 A young girl discovers a hidden magical forest where trees glow and mythical creatures come to life. The camera follows her as she explores. |
Additionally, the creatures I included in my prompt weren’t animated at all, which was disappointing. This lack of adherence to the prompt made the output feel incomplete and less dynamic than I had hoped.
For this reason, I had to repeatedly experiment with various prompts and inputs to get a satisfying result with Stable Video Diffusion.
For my second attempt, I got more specific with the details: "A young girl wanders into a hidden magical forest where towering trees glow with a soft emerald light. As she explores, the camera follows her closely, capturing her awe as mythical creatures spring to life around her: a shimmering unicorn prances through the undergrowth, a mischievous fairy flutters near her shoulder, sprinkling golden dust, and a gentle dragon with iridescent scales soars overhead."
This time, the generated video was noticeably better—the unicorn, fairy, and dragon came to life with their movements, adding the vibrant, magical touch I’d been aiming for all along.
Overall, Stable Video Diffusion has its highs and lows. It’s great at making visuals look realistic, but I had to tweak my prompts a lot to get the animations—like my mythical creatures—moving properly. Once I got the hang of it, the results were much better, but it definitely takes some trial and error to make it work smoothly. It’s a solid tool, just needs a bit more polish!
What Features Impressed Me about Stable Video Diffusion?
Stable Video Diffusion is an AI video model with extensive capabilities that can bring flexibility and creativity to any workflow. Let me break down the core aspects that I value most about it.
High Quality Videos
Stable Video Diffusion comes with two image-to-video models that can both convert static images into all kinds of dynamic, high-resolution clips. Based on latent diffusion architecture and trained on vast datasets, it can follow real-world dynamics and replicate complex visual aspects.
This includes all sorts of character movements, object interactions, changes in environment, etc. For this reason, I can confidently use it to animate any type of still image and get fairly high-quality visuals with smooth transitions.
Multi-View Synthesis
With Stable Video Diffusion, I can render all sorts of dynamic viewpoints from a single image. In other words, instead of settling for 2D viewing, I can get accurate 3D orbital views of any subject or object to produce cinematic visuals that portray shots from different angles and viewpoints.
This also ensures the generated video outputs come with a certain level of depth and richness that will capture the attention of viewers. For example, if I wanted to create a product promotional video to publish online, then this feature would prove to be incredibly handy.
Multiple Customization Options
Very few AI video models let you customize frame rates, so I was glad to see that Stable Video Diffusion offers that. In other words, you can effectively control how many frames the model will generate. In this case, SVD facilitates customizable frame rates that range between 3 to 30 fps.
This way, it becomes easy to adjust the level of motion clarity and fluidity in your video outputs. Besides that, Stable Video Diffusion lets users adjust various aspects like camera motion and even quality level to balance speed and visual fidelity.
Why Do I Think Stable Video Diffusion Is Worth Using?
I will admit that certain noteworthy benefits of using Stable Video Diffusion give it huge relevancy against emerging titans like Runway and Sora. So, let me sum up some of the key reasons why I believe it is worth using:
- Versatile Video Generation: Stable Video Diffusion can adapt to a wide range of video applications. With multiple AI model variations, countless visual styles, and features like multi-view synthesis and customizable fps, I can attest to its versatility as an AI video generator.
- Open-Source Models: Stable Video Diffusion is entirely open-source, which means any developer can access its source code and fine-tune its use for all kinds of different applications. This, in turn, promotes constant development and collaboration within the wider community.
- Fast Video Output: I noticed that Stable Video Diffusion is quicker than most other AI video generation models, making it possible to get results in about one minute or less. So, if there is a need to generate multiple videos in a hurry, then it can be an efficient tool to help save time.
A Better Alternative to Stable Video Diffusion
The downside of Stability AI is that it typically requires users to install it locally, which can be a tedious and complex process. Luckily, I discovered a simpler and more efficient way to access SVD, which is via Pollo AI. This is an all-in-one image and video generation platform that produces visually appealing, high-resolution content in any style.
However, the main highlight of this tool is that it comes integrated with several powerful AI models like Runway, Kling AI, Pixverse, Hailuo, Luma AI, and Wanx AI. Since they are all in one place, I didn’t need to worry about separate pricing models or using multiple platforms for varied outputs! It’s truly the most convenient way to generate videos.
Aside from that, I was very impressed to see that Pollo AI provides access to an extensive range of AI video tools and effects. I was also quite amused by some of the options made available, as I could use them to create all sorts of fun and entertaining novel videos in a flash. Just head over and sign up for a free trial to see for yourself!
Conclusion
Stable Video Diffusion has been in the game for years, and while it is dealing with stiff competitors like Runway and Sora, it is still a worthwhile AI video generator. In my opinion, it is best-suited for animating images with simple motion, so nothing too complex. If you want to try it out, then just open Pollo AI on your browser and check out what SVD can do now!