How to Improve Video Quality with AI: Upscaling to 4K

TL;DR. An AI upscaler increases the resolution of a video and draws in details that were not in the source: a blurry phone clip becomes sharper, an old recording more watchable. It works in the browser, without watermarks, and costs from 8 tokens.

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What upscaling actually does

Ordinary enlargement stretches pixels: the picture gets bigger and blurrier. AI works differently: it has learned what sharp edges, skin, fabric and foliage look like, and it builds the missing details following these patterns.

Hence the main property to understand right away: it does not "reveal" hidden information, it invents plausible information. On most subjects this is exactly what you need.

What improves well
Overall sharpness and detail
Skin, hair, fabric, nature
Compression artifacts
Old low-resolution recordings

When it works best

1. Phone video in a tight format: social networks compress clips, and upscaling partly returns what was lost.
2. Old recordings: digitized tapes, a family archive, clips from the 2000s.
3. Material for editing where the source is below what the project needs.
4. Frames from a video that will go to print or a big screen.

Resolution steps and frame rate

The upscaler has three steps, and you take them not "at the maximum" but for the task:

Step	Where it goes
1080p	social media, YouTube, presentations: enough in most cases
2K	editing, where you need room for cropping
4K	a big screen, printing frames, footage for later cropping

Each next step costs more than the previous one. And there is a separate detail people usually learn after the fact: processing at 60 frames per second costs twice as much as at 30. If the source is shot at 60 fps and the result goes to social media, where it will be 30 anyway, you overpay for nothing.

The input formats are the usual ones: mp4, mov, webm, m4v and even gif.

What it costs and why

You pay for a specific clip, not for a month of access. The base price includes the first second, and each next second adds to it, so a short fragment costs noticeably less than a full-length recording.

The number on the button is visible before the run and changes with the clip length. How spending works: the card about tokens.

A practical order

1. Trim the extra before upscaling. There is no point paying for seconds that will not make the final cut.
2. Start with a short fragment. Ten seconds show whether the model handles your material, and that is cheaper than running everything.
3. Compare before and after on a still frame. The difference shows less in motion than on pause.
4. Do not chase 4K if the clip goes to social media. It will be recompressed there anyway.

Upscale or generate anew

Upscaling wins when the source is basically fine but small: an archive recording, a video from a messenger, a clip downloaded from social media, a frame from an old phone. Here the model has something to rely on, and the result usually pleases.

When there is no source at all and you need a similar shot, it is cheaper to generate the scene anew with a video model. To improve a photo rather than a video, see the AI image upscaling guide.

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Try it. Create an account: new accounts get 6 tokens. That is enough for a test picture; video upscaling starts from 8 tokens and grows with the clip length and the chosen step. Plans are on the pricing page.

FAQ

Will there be a watermark? No. The result downloads as is.

How high can the resolution go? It depends on the source: upscaling enlarges it several times, and the better the original, the better the result. The steps are 1080p, 2K and 4K.

How long does processing take? Longer than generating a picture: the model processes every frame. The longer the clip, the longer the wait.

Can I improve a video downloaded from social media? Technically yes, and it is a common case: social networks compress heavily.

Source: the official description of the ByteDance video upscaler, which lists the 1080p/2K/4K steps, the accepted formats and the surcharge for 60 frames per second.