What you need to know about this new Chinese text-to-video AI model

The short-form video platform, which has more than 600 million active users, announced a new tool on June 6 called “Kling.” Similar to OpenAI's Sora model, Kling can generate videos “up to two minutes long at a frame rate of 30fps and video resolutions up to 1080p,” according to the company's website.

But unlike Sora, which OpenAI has yet to release to the public four months after it was piloted, Kling quickly began allowing people to try out the model for themselves.

I was one of them. I was able to access the model by downloading Kuaishou's video editing tool, registering with a Chinese phone number, joining the waiting list, and filling out an additional form through Kuaishou's user feedback group. The model can't handle prompts written entirely in English, but you can get around that by translating the phrase you want to use into Chinese or including a Chinese word or two.

So, first things first. Here are some results we generated with Kling to give you an idea of ​​what it looks like. Remember Sora's impressive demo video of the Tokyo streets and a cat running through a garden? Here's Kling's take:

Remember that image of the astronaut on the horse in Dall-E? I asked Kling to create a video version as well.

There are a few things worth praising here: none of these videos stray too far from the prompt and seem physically correct, with camera pans, rippling leaves, and the way the horse and astronaut turn to reveal the Earth behind them. The generation process took about three minutes each — not the quickest, but absolutely fine.

But there are some obvious drawbacks: the videos, although in 720p format, look blurry and grainy, Kling sometimes ignores key prompt requests, and most importantly, all videos currently generated are limited to a length of 5 seconds, making them much less dynamic and complex.

But it's not really fair to compare these results to something like the Sora demo that OpenAI has handpicked and made public, and which arguably shows above-average results. These Kling videos were my first attempts with each prompt, and I included few prompt engineering keywords like “8k, photorealism” to fine-tune the results.