Most open source video generation models make you wait. You write a prompt, hit generate, and then sit there hoping the output is what you imagined. If it is not you tweak the prompt and wait again. That loop gets old fast.
Helios works differently. It generates video in real time at 19.5 frames per second on a single GPU. You can see it being created, interrupt mid generation if something looks off, tweak and continue. Up to a full minute of video without starting over every time something does not look right.
With group offloading it runs on around 6GB of VRAM. Its Apache 2.0 licensed, Weights are on HuggingFace right now. Let’s get into what actually makes it work.
What is Helios?
Helios is a video generation model. You give it a text prompt, an image, or an existing video clip and it generates new video from that input. Text to video, image to video, video to video, all three work.
That part is not new. What is new is how long and how fast it is. It generates up to a full minute of video at 19.5 frames per second on a single GPU without the scene falling apart.
It comes in three versions. Helios Base is the highest quality option, best for when you want the best possible output and have the hardware to support it. Helios Distilled is the fastest, built for efficiency when speed matters more than maximum quality. Helios Mid sits between them and is mainly an intermediate checkpoint from the distillation process — functional but not the first choice for most use cases.
For most people starting out Helios Distilled is the practical pick. For anyone who wants the best output Helios Base is the one.
6GB VRAM Is All You Need
This is the part that surprised me most when I first looked at Helios. A 14B model generating minute long videos at real time speed sounds like something that needs a rack of H100s. And running it at full capacity on a single H100 is still the recommended path for best performance.
But Helios supports group offloading, that means the model moves parts of itself between your GPU and system RAM during inference instead of keeping everything loaded on the GPU at once. The tradeoff is some speed. The benefit is dropping VRAM requirements down to around 6GB.
6GB is a GTX 1060. A laptop GPU. Hardware that millions of people already own.
That does not mean the output will be identical to running it on a full H100 setup. It will be slower and you will feel that on longer generations. But for experimenting, testing prompts, and understanding what the model can do, a consumer GPU is genuinely enough.
For anyone who does not have local hardware at all Helios is also available on HuggingFace Spaces where you can try it directly in your browser.
Also Read: Industry-Grade Open-Source AI Video Models That Look Scarily Realistic
Three versions and which one to pick
Helios comes in three versions and the differences actually matter depending on what you are trying to do.
- Helios Base is the highest quality option. If you want the best possible output and your hardware can handle it this is the one to use. No compromises on quality, full v-prediction training, standard CFG. The go-to for anyone who needs production level results.
- Helios Distilled is the fastest. Built for efficiency through a more aggressive sampling pipeline which means faster generation at the cost of some quality compared to Base. For most people experimenting locally this is the practical starting point. Faster feedback, less waiting, good enough quality to evaluate what the model can actually do.
- Helios Mid is an intermediate checkpoint from the process of distilling Base into Distilled. It works but it is not really intended as a final model — more of a byproduct of the training pipeline that the team released anyway. Functional but not the first choice for most use cases.
My recommendation: Start with Helios Distilled. If the quality satisfies what you need stick with it. If you need more move to Helios Base when your hardware allows.
How to run it
The quickest way to try Helios without any setup is the HuggingFace Spaces demo. Just open it in your browser and start generating. No installation, no GPU required.
If you want to run it locally the setup is straightforward. Clone the repo, create a conda environment, install PyTorch for your CUDA version, and run the install script. Weights download automatically from HuggingFace or ModelScope.
Once set up, inference scripts are ready for all three versions covering text to video, image to video and video to video. Pick your version and run the corresponding script.
For developers who prefer working within existing pipelines Helios already has day one support for Diffusers, SGLang and vLLM. Pick whichever fits your current workflow.
One practical note — before running your own prompts go through the sanity check first. It saves a lot of time if something is wrong with your hardware or software setup.
ComfyUI support is not official yet but given how the community works around models like this it is likely coming. Worth keeping an eye on the GitHub for community contributions.
Supported platforms: Windows via WSL, Linux, macOS with Apple Silicon
A big move towards real time video generation
Real time video generation that runs on consumer hardware and generates minute long coherent footage is not something the open source space had six months ago. Helios changes that.
It is a fresh release so expect rough edges, prompts that do not always behave, and a community that is still figuring out the best workflows. That is normal for something this new.
But Apache 2.0, weights on HuggingFace, day one framework support, and 6GB VRAM accessibility on a 14B model is a combination that does not come along often. The ceiling on what individual developers and small teams can build just got higher.
