Nvidia Image Scaling vs DLSS

How does DLSS (Deep Learning Super Samspling) compare to Nvidia Image Scaling (NIS)? Here's the ultimate guide to help you out.

Nvidia’s relatively new upscaling technology, DLSS, is quite popular, and you can probably find it in most games’ settings nowadays. It’s a great way to boost FPS without sacrificing image quality.

However, DLSS’s downside is that it does not work on all Nvidia cards, but Nvidia Image Scaling (NIS) does. Both have the same goal, but they work pretty differently.

So what’s the catch? Which one of these two features is better for getting more FPS in-game?

Well, dive right into this article, and let’s explore the benefits of using one or the other feature.

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DLSS – Deep Learning Super Sampling

Deep Learning Super Sampling is one of Nvidia’s proudest software innovations. It utilizes an RTX card’s Tensor Cores to upscale an image through a complex deep learning network (AI).

With this AI, the images that DLSS outputs are similar to native resolution and, in some cases, even better than native.

How does DLSS achieve this?

Nvidia DLSS

When DLSS is enabled, a game renders at a lower resolution (analogous to the native resolution). At the same time, the Tensor Cores put in the work to develop an image that’s closer to the native resolution.

Of course, this short explanation is extremely simplified, but what goes on in the Nvidia GPU is definitely more complex. Either way, it goes without saying that DLSS is extremely useful as it improves performance while delivering a high-quality image.

How much performance or quality a user can get depends on the setting they pick in-game: Ultra Performance, Performance, Balanced, and Quality.

However, DLSS is not all good. We mentioned Tensor Cores a couple of times now, and this piece of hardware can only be found in Nvidia’s RTX 2000 and 3000 graphics cards. Future Nvidia cards will most probably support DLSS too. In other words, DLSS can’t be used in non-RTX GPUs.

It’s also important to note that DLSS needs to be integrated per game by developers and Nvidia. So, even though the supported game list is expanding every day, you may still end up with a game that doesn’t have this feature.

But this is where NIS comes in!

NIS – Nvidia Image Scaling

NIS is a feature that’s been with Nvidia GPUs for some time now, but it hasn’t gotten any attention until AMD released Radeon Super Resolution, a similar feature.

Today, NIS is much more effective at upscaling because it’s been updated with a “6-tap filter with four directional scaling and adaptive sharpening filters”. This boosts image quality and performance.

Here’s a video from KitGuruTech showcasing NIS in various games:

What differentiates NIS from DLSS is that it doesn’t require proprietary hardware (like RTX) and is driver-based. In other words, (almost) all Nvidia graphics cards with the appropriate driver can use NIS.

Unfortunately, AMD GPU users are unable to use this feature.

Also, note that Nvidia Image Scaling does not need per-game integration; instead, it can be activated through GeForce Experience. In other words, it can be activated for any game.


When both of these features are available, which one should you use?

Let’s look at some of the advantages and disadvantages:

  • Image Quality – With Nvidia’s Tensor Cores and deep learning, the final image is of much higher quality compared to using NIS.
  • Performance – Again, thanks to DLSS’ AI upscaling, the performance boost is superior to NIS.
  • Game support – NIS supports many games simply because it’s enabled through Nvidia’s driver, while DLSS needs to be available in-game to be used.
  • Supported Hardware – DLSS is proprietary to RTX GPUs, while NIS can be enabled on most Nvidia cards.

Overall, DLSS is the better upscaling technology. It’s a complex upscaling deep learning network, so naturally, it provides better performance and quality.

So, here’s the deal:

If you possess an RTX graphics card in your computer and DLSS is offered in a game, make use of it. If you lack an RTX GPU or DLSS is unavailable, yet you require that additional increase in frames per second, utilize NIS.


In terms of updates, both DLSS and NIS have a future. How long this future will last, we can’t precisely know.

DLSS has the potential to be expanded into a so much more powerful AI, but since it relies on hardware, it may not be that future-proof. When (or if) DLSS 3.0+ comes out, it may need a more powerful RTX card to use it.

On the other hand, NIS is a much simpler upscaling solution and software-based, making it a lot easier to update, i.e., be future-proof.

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Branko Gapo

Keeping up with the incredibly fast evolution of computer technology is impossible. That is why Branko will be using his knowledge on this matter to share news and information on all the latest essential technological innovations and advancements.