Nvidia Image Scaling vs DLSS

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

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

So what’s the catch? Which one of these two characteristics is superior for obtaining more FPS in-game?

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

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 an intricate deep learning network (AI).

Using this AI, the images generated by DLSS are comparable to the initial quality and, at times, even better than the original.

How does DLSS accomplish this?

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

Of course, this concise explanation is highly simplified, but what goes on in the Nvidia GPU is certainly more complex. Either way, it goes without saying that DLSS is remarkably beneficial as it enhances 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 Outstanding.

However, DLSS is not all wonderful. 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. Upcoming Nvidia cards will most likely 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 growing every day, you may still end up with a game that doesn’t have this crucial feature.

But this is where NIS enters!

NIS – Nvidia Image Scaling

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

Today, NIS is considerably more efficient at upscaling because it’s been updated with a “6-tap filter with four directional scaling and adaptive sharpening filters“. This enhances image quality and speed.

Here’s an excerpt from KitGuruTech showcasing NIS in various games:

What differentiates NIS from DLSS is that it doesn’t require specialized 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 incapable of utilizing this feature.

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

NIS vs. DLSS

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

Let’s explore a few of the benefits and drawbacks:

• 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 superior upscaling technology. It’s a complex upscaling deep learning network, so naturally, it provides better performance and excellence.

So, here’s the circumstance:

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 need that additional boost in frames per second, employ NIS.

Future-proof?

In terms of updates, both DLSS and NIS have a future. How long this future will endure, we can’t exactly 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 lasting. When (or if) DLSS 3.0+ comes out, it may need a more advanced RTX card to use it.

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