AI video models and generators are waiting for their “ghibli moments” (the viral moment that made AI image generation mainstream overnight).

Sora's launch came close, but with the app shut down in early 2026, we're not convinced it stuck.

This report aims to paint a picture of the state of AI in early 2026 and all its aspects: the top models, the AI SaaS tools and the different technologies used.

The goal is not to drown you in benchmarks, but to explain in plain terms where this category stands and what you can practically do with these tools today.

AI Video Models

We start with the foundational AI models (Veo, Sora, Seedance,etc.), which are separate from the AI video platforms like Synthesia and HeyGen that are often built on top of them.

See our dedicated section on that distinction further down.

Below are the top 14 companies shipping AI video models and the rankings of their latest models by quality of the video output (as per Video Arena).

Here is something worth noting as well, beyond rankings:

There is a difference between these models that’s often overlooked but matters to people tinkering with them and wanting to customize or train their own model.

There are 3 types of AI models (for video generation but also image or text in LLM):

People often say Open Source but really mean Open Weight since almost no top AI models are truly Open Source.

LTX-2 comes closest since Lightricks released weights and training code, but the training data is not fully disclosed.

Note: Model weights are the millions of numerical values learned during training that define how the model thinks. Essentially the AI's knowledge and capability stored as a file you can download and run on your own hardware.

Pricing vs Quality

Most people won’t simply look at the model with the highest quality and run with it. 

At scale, pricing matters just as much as quality. A model that's good enough at a lower cost per second will often beat the

Grok seems to be a noteable top tier model that's on the affordable side too.

While Google Veo and OpenAI Sora are on the more expensive side. It's worth noting that cost can vary a lot depending on the model and setup you have.

AI Video models Vs AI Video Generator Tools

This is the other important distinction to make in this space that we alluded to earlier.

What we’ve listed so far are AI video models. 

That’s the actual technology doing the work if you will.

Now, most of them offer a user-friendly interface and platform for people to be able to use them.

So for example you can go right now in the Gemini app, select the video tool and use their Veo model that way.

Another way to access these models are through AI video generators tools

These can give you access to several models in one place or simply have more customization options and a more AI video dedicated interface.

Here are some of the main ones:

Some tools on the landscape above, like Pika and Hailuo, also develop their own underlying models, blurring the line between the two categories.

They allow you to use a range of models to create and edit the video, or to generate from an image for instance.

Some are specialized in Avatar generation some in AI lookalike versions of you, some in video editing or clipping,etc.

Below is an attempt at placing these most popular tools in a category graph to help you understand their different uses and who they cater to:

Of course this is somewhat subjective but should help you know which to explore for your personal use case.

AI Models Technologies

The last aspect of AI video models we want to showcase is the nitty gritty of how they work at the top level.

We mean the specific process and steps AI video models go through to generate a video.

There are 3 technical approaches used today:

Note: most SOTA models now use a DiT approach as it tends to provide the best quality for a relatively fast generation speed.

But depending on your use case you might want to experiment with another approach.

Here is the same comparison in a different visual format:

Most production teams won't choose a model based on architecture alone, but understanding it helps explain why outputs differ across tools at similar price points.

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