Nvidia Image Scaling vs DLSS

Nvidia Image Scaling vs DLSS | Which one is Better?

Most of the people wanted to know that in between Nvidia Image Scaling vs DLSS, which is better in different ways. In this article, I will provide you with the opinion that which card is best for you according to your usage.

So DLSS is a relatively recent upscaling technique developed by Nvidia, is fairly popular, and it is likely that you may find it in the settings of the majority of games these days. It is an excellent method for increasing FPS without lowering the visual quality in any manner.

The disadvantage of DLSS is that it is not compatible with all Nvidia cards; however, Nvidia Image Scaling (NIS) is universally supported. Both will get you to the same place, but how they get there is very different.

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So, what’s the catch, if you will? Which of these two characteristics contributes to a higher overall frame rate when playing the game? So, without further ado, let’s jump right into this post and discuss the advantages of utilizing any one of these features.

Functions of DLSS (Deep Learning Super Sampling)

Deep Learning Super Sampling is one of the software developments that Nvidia is most pleased with. It does this by running an image through a sophisticated deep learning network while utilising the Tensor Cores of an RTX card (AI).

Functions of DLSS Deep Learning Super Sampling
DLSS (Deep Learning Super Sampling)

Using this AI, DLSS is able to produce pictures that have a resolution that is comparable to native resolution, and in some circumstances, even better than native resolution.

Now the question is that how does DLSS achieve this?

When Deep Learning Super Sampling is turned on, a game will render at a reduced resolution (analogous to the native resolution). While this was going on, the Tensor Cores were hard at work creating an image with a resolution that was much more comparable to the native one.

This brief explanation is, of course, grossly oversimplified, but the processes that take place within the Nvidia GPU are unquestionably more complicated. In either case, it should come as no surprise that DLSS is rather beneficial because it enhances performance while simultaneously producing images of a high quality.

The user may choose from four different settings in game: Ultra Performance, Performance, Balanced, and Quality. These settings determine how much performance or quality the user receives.

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However, there are certain drawbacks to using DLSS. Tensor Cores have been brought up a few times already, and it should be noted that Nvidia’s RTX 2000 and 3000 graphics cards are the only ones that have this particular piece of silicon. It is quite likely that future Nvidia graphics cards will also feature DLSS. To put it another way, non RTX GPUs do not support the use of DLSS.

It is also essential to keep in mind that DLSS must be implemented individually for each game by the creators and Nvidia. It is possible that you will purchase a game that does not have this function, despite the fact that the list of games that are supported continues to grow every day.

Functions of NIS (Nvidia Image Scaling)

NIS is a function that has been available on GPUs manufactured by Nvidia for some time now; nevertheless, it hasn’t received much notice until AMD developed Radeon Super Resolution, which is a capability that is quite similar to NIS.

Functions of NIS Nvidia Image Scaling
NIS (Nvidia Image Scaling)

The upscaling capabilities of NIS have been significantly improved thanks to a recent update that included the addition of a “6 tap filter with four directional scaling and adaptive sharpening filters.” The performance and visual quality both benefit from this.

NIS is a driver based system, unlike DLSS, which mandates the use of specialised hardware (like RTX). This is the primary distinction between the two. To put it another way, NIS is compatible with (nearly) all Nvidia graphics cards if the necessary driver is installed.

Users using AMD GPUs are unable to take advantage of this functionality, unfortunately.

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Additionally, it is important to note that activating Nvidia Image Scaling does not need individual game integration; rather, it may be done so through GeForce Experience. In other words, it is applicable to any game and may be engaged for any of them.

Nvidia Image Scaling vs DLSS

Image obtained from Digital Trends comparing DLSS, FSR, and NIS in Call of Duty: Vanguard and Deathloop.

Which of these features should you make use of when it is possible to access them both?

Let’s take a look at some of the positives and negatives of this situation:

  • Image Quality: In comparison to when NIS was used, the quality of the final image produced by Nvidia’s Tensor Cores and deep learning is much improved.
  • Performance: Once again, the performance advantage provided by DLSS’s AI upscaling is better to that provided by NIS.
  • Game Support: NIS supports a wide variety of games due to the fact that it is enabled by Nvidia’s driver, whereas DLSS can only be utilised if the game itself has the option to do so.
  • Compatibility with Hardware: DLSS is exclusive to RTX GPUs, whereas NIS may be activated on the vast majority of Nvidia cards.

In general, the DLSS upscaling technology is superior than other options. Given that it is an intricate upscaling deep learning network, it is only logical that it delivers superior performance and quality.

If you have an RTX card installed in your PC and there is a game that supports DLSS, you should utilise it. Use NIS if you require an additional increase in frames per second but don’t have an RTX GPU and DLSS isn’t an option for you.

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Graphics Card & Game Support

It is essential to have a solid understanding of the distinctions between Nvidia Image Scaling vs DLSS before moving on to our analyses of the performance and comparisons of the image quality. The DLSS is the one that requires the most attention to detail. It is only compatible with graphics cards from the Nvidia RTX 20 and RTX 30 series, and it is only functional in games that support it. Because the developers are required to include it, you won’t be able to incorporate it in your game of choice if you don’t find a DLSS option there.

There is a compelling explanation behind that. The image is enhanced with the utilisation of A.I. by DLSS. Graphics cards in the RTX 20 and 30 series include specialised artificial intelligence accelerators called Tensor cores. Each new update of the Nvidia driver software incorporates an artificial intelligence model that is capable of running on the Tensor cores and upscales the image in real time.

During the upscaling process, DLSS makes use of temporal (time based) information in addition to the A.I. model. This helps to eliminate shimmering, ghosting, and other visual artefacts.

The NIS and FSR operate in quite different ways. Both of these are methods of spatial upscaling rather than temporal ones. Upscaling in FSR and NIS is determined not by collecting a number of frames and utilising temporal information as a basis, but rather by using the frame that is now being displayed as a point of reference. This results in an increased amount of ghosting and shimmering, in addition to other visual distortions.

Both features do not make use of any artificial intelligence. Instead, FSR and NIS will upscale the picture depending on the frame that is currently being produced, and then they will apply a sharpening filtering to make it appear as though the image is operating at a higher resolution.

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Both FSR and NIS are quite comparable in terms of their technological aspects. The sole distinction between the two is that NIS performs the upscaling and sharpening procedures in a single pass whereas FSR divides these processes into two separate passes.

Final Thoughts

In the technological fight between Nvidia Image Scaling vs DLSS, we have concluded that both DLSS and NIS both have a future in terms of improvements to their respective systems. We are unable to provide an exact estimate for how long this future will continue.

All three upscaling techniques make some kind of compromise, whether it is in terms of image quality, performance, or GPU support. DLSS is the superior choice if you have a GPU that is compatible with it. Having said that, FSR and NIS are both good choices to consider if you don’t mind making a small concession in terms of image quality.

However, in contrast to DLSS and FSR, Image Scaling may be used with any game; it is not limited to just those titles for whom the creators have included support. You don’t even need one of the top graphics cards with all of the RTX gubbins; any Nvidia GPU from the Maxwell generation and onwards will work (essentially, a GTX 745 or higher).

DLSS has the potential to be extended into an AI that is so much more powerful; but, because it relies on hardware, it may not be as future proof as other AI approaches. It’s possible that in order to use DLSS 3.0+ you’ll need an RTX card with a higher performance rating.

On the other hand, NIS is an upscaling solution that is far easier to implement and is software based. Because it is so much simpler to upgrade, we can say that it is future proof.

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FAQs for Nvidia Image Scaling vs DLSS

Is DLSS or Image Scaling better?

Each upscaling mode compromises image quality, performance, and GPU support. DLSS is ideal for supported GPUs. FSR and NIS are good choices if you’re willing to sacrifice image quality.

Is Nvidia Image Scaling the same as DLSS?

Unlike DLSS and indeed, FSR Image Scaling works on any game, not just those supported by the makers. Nvidia GPUs from the Maxwell generation (GTX 745 or above) will function.

Should you use Nvidia Image Scaling?

“85% or 77%” provides the finest gaming experience without sacrificing image quality. This demo explains how NVIDIA Image Scaling affects gameplay.

Does DLSS hurt quality?

We noticed that DLSS 3 decreased overall quality, which is easy to overlook because to the frame rate gains, but some quality issues are hard to ignore.

Does DLSS reduce FPS?

NVIDIA DLSS 3 Increases FPS by 3x, 4x but Decreases Detail and Increases Latency. DLSS 3, a sophisticated upscaling algorithm that enhances performance by nearly 3x in supported titles, is a hallmark of NVIDIA’s RTX 40 series graphics cards.