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'''Deep Learning Super Sampling''' ('''DLSS''') is a suite of [[Real-time computing|real-time]] [[deep learning]] image enhancement and [[Image scaling|upscaling]] technologies developed by [[Nvidia]] that are available in a number of [[video game]]s. The goal of these technologies is to allow the majority of the [[graphics pipeline]] to run at a lower [[Display resolution|resolution]] for increased performance, and then infer a higher resolution image from this that approximates the same level of detail as if the image had been rendered at this higher resolution. This allows for higher graphical settings and/or [[frame rates]] for a given output resolution, depending on user preference.<ref name=":2">{{cite web|url=https://www.digitaltrends.com/computing/everything-you-need-to-know-about-nvidias-rtx-dlss-technology/|title=Nvidia RTX DLSS: Everything you need to know |publisher=[[Digital Trends]]|date=2020-02-14|access-date=2020-04-05|quote=Deep learning super sampling uses artificial intelligence and machine learning to produce an image that looks like a higher-resolution image, without the rendering overhead. Nvidia's algorithm learns from tens of thousands of rendered sequences of images that were created using a supercomputer. That trains the algorithm to be able to produce similarly beautiful images, but without requiring the graphics card to work as hard to do it.}}</ref>
All generations of DLSS are available on all [[Nvidia RTX|RTX]]-branded cards from Nvidia in supported titles. However, the [[Frame Generation]] feature is only supported on [[GeForce 40 series|40 series]] GPUs or newer and [[Multi Frame Generation]] is only available on [[GeForce 50 series|50 series]] GPUs.<ref name=":3">{{Cite web |title=Introducing NVIDIA DLSS 3 |url=https://www.nvidia.com/en-us/geforce/news/dlss3-ai-powered-neural-graphics-innovations/ |access-date=2022-09-20 |website=NVIDIA |language=en-us}}</ref><ref name=":6">{{Cite web |title=NVIDIA DLSS 4 Introduces Multi Frame Generation & Enhancements For All DLSS Technologies |url=https://www.nvidia.com/en-us/geforce/news/dlss4-multi-frame-generation-ai-innovations/ |access-date=2025-01-14 |website=NVIDIA |language=en-us
== History ==
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In January 2025, Nvidia stated that there are over 540 games and apps supporting DLSS, and that over 80% of [[Nvidia RTX]] users activate DLSS.<ref>{{Cite web |date=2025-01-16 |title=DLSS enabled by over 80% of GeForce RTX gaming GPU owners, claims Nvidia |url=https://www.pcgamesn.com/nvidia/dlss-80-percent |access-date=2025-01-31 |website=PCGamesN |language=en-US}}</ref>
In March 2025, there were more than 100 games that support DLSS 4, according to Nvidia.<ref>{{Cite web |last=Mujtaba |first=Hassan |date=2025-03-13 |title=NVIDIA DLSS 4 Now In Over 100 Games With More Titles Coming Soon, Neural Shading Support For DirectX Arriving Next Month |url=https://wccftech.com/nvidia-dlss-4-now-in-over-100-games-more-titles-coming-soon-neural-shading-support-directx-next-month/ |access-date=2025-05-20 |website=Wccftech |language=en-US}}</ref> By May 2025, over 125 games supported DLSS 4.<ref>{{Cite web |last=Mujtaba |first=Hassan |date=2025-05-19 |title=NVIDIA DLSS 4 Now Available In Over 125 Games & Apps, DOOM: The Dark Ages Path Tracing Update In June & Even More DLSS Titles |url=https://wccftech.com/nvidia-dlss-4-125-games-doom-the-dark-ages-path-tracing-update-june-more-dlss-titles/ |access-date=2025-05-20 |website=Wccftech |language=en-US}}</ref><ref>{{Cite web |last=Palumbo |first=Alessio |date=2025-05-19 |title=NVIDIA DLSS 4 Multi Frame Generation and Other RTX Updates Shown Off for Upcoming and Existing PC Games |url=https://wccftech.com/nvidia-dlss-4-multi-frame-generation-and-other-rtx-updates-shown-off-for-upcoming-and-existing-pc-games/ |access-date=2025-05-20 |website=Wccftech |language=en-US}}</ref>
The first [[video game console]] to use DLSS, the [[Nintendo Switch 2]], was released on June 5, 2025.<ref>{{Cite news |last=Stuart |first=Keith |date=2025-06-05 |title=The Nintendo Switch 2 is out – here's everything you need to know |url=https://www.theguardian.com/games/2025/jun/05/the-nintendo-switch-2-is-out-today-heres-everything-you-need-to-know |access-date=2025-06-09 |work=The Guardian |language=en-GB |issn=0261-3077}}</ref>
=== Release history ===
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|"1.9" (unofficial name)||August 2019||DLSS 1.0 adapted for running on the CUDA shader cores instead of tensor cores, used for ''[[Control (video game)|Control]]''<ref name="eurogamer"/><ref name="techspot"/><ref name="nividiacontrol">{{cite web |last1=Edelsten |first1=Andrew |title=NVIDIA DLSS: Control and Beyond |url=https://www.nvidia.com/en-us/geforce/news/dlss-control-and-beyond/ |publisher=Nvidia |access-date=11 August 2020 |date=30 August 2019 |quote=Leveraging this AI research, we developed a new image processing algorithm that approximated our AI research model and fit within our performance budget. This image processing approach to DLSS is integrated into Control, and it delivers up to 75% faster frame rates.}}</ref>
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|2.0||April 2020||An AI accelerated form of [[Temporal anti-aliasing|TAA]]U using Tensor Cores, and trained generically<ref name="control2">{{cite web|url=https://www.techquila.co.in/nvidia-dlss-2-control-review/|title=NVIDIA DLSS 2.0 Review with Control – Is This Magic?|work=TechQuila |publisher=techquila.co.in|date=2020-04-05|access-date=2020-04-06}}</ref>
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|3.0
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|Ultra Quality<ref name=":5">{{cite web |title=NVIDIA preparing Ultra Quality mode for DLSS, 2.2.9.0 version spotted |url=https://videocardz.com/newz/nvidia-preparing-ultra-quality-mode-for-dlss-2-2-9-0-version-spotted |access-date=2021-07-06 |website=VideoCardz.com |language=en-US}}</ref><sub> (unused)</sub>
|1.32x
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|Quality
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DLSS 2.0 uses a [[Convolutional neural network|convolutional]] [[Autoencoder|auto-encoder]] [[neural network]]<ref name="nvidia20" /> trained to identify and fix temporal artifacts, instead of manually programmed heuristics as mentioned above. Because of this, DLSS 2.0 can generally resolve detail better than other TAA and TAAU implementations, while also removing most temporal artifacts. This is why DLSS 2.0 can sometimes produce a sharper image than rendering at higher, or even native resolutions using traditional TAA. However, no temporal solution is perfect, and artifacts (ghosting in particular) are still visible in some scenarios when using DLSS 2.0.
Because temporal artifacts occur in most art styles and environments in broadly the same way, the neural network that powers DLSS 2.0 does not need to be retrained when being used in different games. Despite this, Nvidia does frequently ship new minor revisions of DLSS 2.0 with new titles,<ref>{{Cite web|title=NVIDIA DLSS DLL (2.3.7) Download|url=https://www.techpowerup.com/download/nvidia-dlss-dll/|access-date=2022-02-10|website=TechPowerUp|language=en}}</ref> so this could suggest some minor training optimizations may be performed as games are released, although Nvidia does not provide changelogs for these minor revisions to confirm this. The main advancements compared to DLSS 1.0 include: Significantly improved detail retention, a generalized neural network that does not need to be re-trained per-game, and ~2x less overhead (~
It should also be noted that forms of TAAU such as DLSS 2.0 are not [[Video scaler|upscalers]] in the same sense as techniques such as ESRGAN or DLSS 1.0, which attempt to create new information from a low-resolution source; instead, TAAU works to recover data from previous frames, rather than creating new data. In practice, this means low resolution [[Texture mapping|textures]] in games will still appear low-resolution when using current TAAU techniques. This is why Nvidia recommends game developers use higher resolution textures than they would normally for a given rendering resolution by applying a mip-map bias when DLSS 2.0 is enabled.<ref name="NVIDIA" />
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=== DLSS 4.0 ===
The fourth generation of Deep Learning Super Sampling (DLSS) was unveiled alongside the [[GeForce RTX 50 series]]. DLSS 4 upscaling uses a new vision [[Transformer (deep learning architecture)|transformer]]-based model for enhanced image quality with reduced ghosting and greater image stability in motion compared to the previous [[convolutional neural network]] (CNN) model.<ref>{{cite web |last1=Leadbetter |first1=Richard |date=January 7, 2025 |title=Hands-on with DLSS 4 on Nvidia's new GeForce RTX 5080 |url=https://www.eurogamer.net/digitalfoundry-2025-hands-on-with-dlss-4-on-nvidias-new-geforce-rtx-5080 |website=Eurogamer |language=en-GB |access-date=January 7, 2025}}</ref> DLSS 4 allows a greater number of frames to be generated and [[Frame interpolation|interpolated]] based on a single traditionally rendered frame. This form of frame generation called Multi Frame Generation is exclusive to the GeForce RTX 50 series while the [[GeForce RTX 40 series]] is limited to one interpolated frame per traditionally rendered frame. According to Nvidia, this technique will increase performance by up to 800% while retaining low latency with [[Nvidia Reflex]].<ref name=":62">{{Cite web |title=NVIDIA Blackwell GeForce RTX 50 Series Opens New World of AI Computer Graphics |url=https://nvidianews.nvidia.com/news/nvidia-blackwell-geforce-rtx-50-series-opens-new-world-of-ai-computer-graphics |access-date=2025-01-07 |website=NVIDIA Newsroom |language=en-us}}</ref> Nvidia claims that DLSS 4x Frame Generation model uses 30% less video memory with the example of ''[[Warhammer 40,000: Darktide]]'' using 400MB less memory at 4K resolution with Frame Generation enabled.<ref>{{cite web |last1=Lin |first1=Henry |last2=Burnes |first2=Andrew |date=January 6, 2025 |title=Nvidia DLSS 4 Introduces Multi Frame Generation & Enhancements For All DLSS Technologies |url=https://www.nvidia.com/en-us/geforce/news/dlss4-multi-frame-generation-ai-innovations/ |website=Nvidia |language=en-US |access-date=January 7, 2025}}</ref> Nvidia claims that 75 games will integrate DLSS 4 Multi Frame Generation at launch, including ''[[Alan Wake 2]]'', ''[[Cyberpunk 2077]]'', ''[[Indiana Jones and the Great Circle]]'', and ''[[Star Wars Outlaws]]''.<ref>{{cite web |last1=Mujtaba |first1=Hassan |date=January 6, 2025 |title=Nvidia DLSS 4 Delivers An Insane 8x Performance Boost Versus DLSS 3 With Multi Frame Generation Technology, Enhanced Upscaling For RTX 20 & Above |url=https://wccftech.com/nvidia-dlss-4-8x-faster-dlss-3-multi-frame-generation-enhanced-upscaling-rtx-20-above/ |website=Wccftech |language=en-US |access-date=January 7, 2025}}</ref>
{| class="wikitable plainrowheaders" style="text-align:left; font-size:90%;
! style="width:12em; height:3em;" |
! [[GeForce RTX 20 series]]
! [[GeForce RTX 30 series]]
! [[GeForce RTX 40 series]]
! [[GeForce RTX 50 series]]
|-
! scope="row" style"height:2em;" | Transformer Model
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== Anti-aliasing ==
DLSS requires and applies its own [[anti-aliasing]] method. Thus, depending on the game and quality setting used, using DLSS may improve image quality even over native resolution rendering.<ref>{{Cite web |last=Smith |first=Matthew S. |date=2023-12-28 |title=What Is DLSS and Why Does it Matter for Gaming? |url=https://www.ign.com/articles/what-is-nvidia-dlss-meaning |access-date=2024-06-13 |website=IGN |language=en}}</ref> It operates on similar principles to [[Temporal anti-aliasing|TAA]]. Like TAA, it uses information from past frames to produce the current frame. Unlike TAA, DLSS does not sample every pixel in every frame. Instead, it samples different pixels in different frames and uses pixels sampled in past frames to fill in the unsampled pixels in the current frame. DLSS uses machine learning to combine samples in the current frame and past frames, and it can be thought of as an advanced and superior TAA implementation made possible by the available tensor cores.<ref name="NVIDIA" /> [[Nvidia]] also offers [[Deep Learning Anti-Aliasing]] (DLAA), which provides the same AI-driven anti-aliasing DLSS uses, but without any upscaling or downscaling
== Architecture ==
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The use of DLSS Frame Generation may lead to increased [[input latency]],<ref>{{Cite web |date=2023-11-21 |title=When a high frame rate can lose you the game |url=https://www.digitaltrends.com/computing/when-frames-dont-win-games/ |access-date=2024-07-09 |website=Digital Trends |language=en}}</ref> as well as [[visual artifacts]].<ref>{{Cite web |date=2023-03-08 |title=Nvidia DLSS 3 Revisit: We Try It Out in 9 Games |url=https://www.techspot.com/article/2639-dlss-3-revisit/ |access-date=2024-07-09 |website=TechSpot |language=en-US}}</ref> It has also been criticized that by implementing DLSS in their games, game developers no longer have an incentive to optimize them so that they also run smoothly in native resolution on modern PC hardware. For example, for the game ''[[Alan Wake 2]]'' in [[4K resolution]] at the highest graphics settings with [[Ray tracing (graphics)|ray tracing]] enabled, the use of DLSS in Performance mode is recommended even with graphics cards such as the [[Nvidia GeForce RTX 4080]] in order to achieve 60 fps.<ref>{{Cite web |date=2023-10-26 |title=Alan Wake 2 on PC is an embarrassment of riches |url=https://www.digitaltrends.com/computing/alan-wake-2-pc-performance/ |access-date=2024-07-09 |website=Digital Trends |language=en}}</ref>
The transformer-based AI
== See also ==
* [[GPUOpen#FidelityFX Super Resolution|FidelityFX Super Resolution]] – competing technology from [[AMD]]
* [[Intel XeSS]] – competing technology from [[Intel]]
* [[PlayStation Spectral Super Resolution]] – similar technology from [[
== References ==
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[[Category:Nvidia]]
[[Category:Anti-aliasing algorithms]]
[[Category:Artificial intelligence]]
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