NVIDIA DLSS Transformer: More Performance, Less VRAM – An In-Depth Analysis of the New Era of Upscaling

1. Introduction: DLSS Evolving and Saving Your Motherboard's VRAM!

Hey gamers! Anyone who plays games knows that NVIDIA's DLSS (Deep Learning Super Sampling) is like an official cheat code : it boosts FPS and makes graphics look beautiful, even at lower resolutions. The magic? It renders the game at a lower resolution and uses artificial intelligence to intelligently "stretch" the image, delivering the fluid and immersive experience we all love. [1] With games becoming increasingly demanding and Ray Tracing becoming rampant, DLSS has become a true hero for our gaming. [4]

NVIDIA has just dropped a bombshell: the official release of the DLSS Transformer model as part of SDK 310.3.0. [5] This isn't just a small patch; the Transformer model is the heart of DLSS 4 , and it promises two gifts for us: an absurd boost in performance and a significant reduction in VRAM consumption . [2]

And why is this VRAM optimization so important? Simple: many people still have video cards with 8 GB of VRAM or less, and these little beauties struggle to run the newest games at max settings. [5] NVIDIA is keeping an eye on this and wants to give these GPUs a breather. Even if the savings in megabytes seems small, every MB counts when your card is at its limit. [14] This optimization is a masterstroke to extend the lifespan of our hardware , allowing more people to enjoy new releases without having to spend a fortune on a new card. It's DLSS not only speeding up the game, but also managing VRAM, which further enhances the value of older or entry-level RTX cards. It's NVIDIA showing that it cares about its players and wants to keep everyone on Team GeForce!

2. The Technological Leap: Goodbye CNN, Hello Transformer!

NVIDIA has made a radical change to the artificial intelligence behind DLSS: it has replaced the old Convolutional Neural Networks (CNNs) with Transformer models, which are much more advanced. And this change is not only for DLSS Super Resolution, but also for Ray Reconstruction and Deep Learning Anti-Aliasing (DLAA)! [2]

CNNs, which we used in previous versions of DLSS, were like a detective that only looked at neighboring pixels to try to guess what was missing from the image. It worked, but sometimes it produced strange artifacts, especially in scenes with a lot of action or fine details. [3] The Transformer model is a different story! It analyzes the relationship between all the pixels in a frame and also uses information from several previous frames. [5] It's like having an eagle's eye view of the scene, which allows you to reconstruct details that previously disappeared or became blurred with CNNs. [15]

This switch from CNNs to Transformers isn't just an adjustment; it's a revolution in how DLSS processes images . Transformers, which were famous for language processing, are now showing their power in graphics. NVIDIA spent six years training and refining this model on its supercomputers [18], which shows how much they invest in AI. This proves that AI is the future of NVIDIA, not only in games, but in all computing. [1] We are seeing DLSS mature, moving towards a more "intelligent" upscaling that understands the context of the scene and movement, not just pixel patterns. NVIDIA is consolidating itself as a leader not only in hardware, but also in the application of cutting-edge AI to graphics.

The Transformer model delivers absurd image stability , eye-popping lighting details, and most importantly, motion sharpness like never before. [2] It solves those annoying problems from the old DLSS, like blurry textures in motion, "trails" on distant objects, and the infamous "ghosting" (ghost images). [3] NVIDIA doubled the model's parameters and quadrupled its processing power, which means image quality so good that it's sometimes impossible to distinguish it from native, or even better! [6] And people are saying that Ray Reconstruction, which previously seemed "oily" with CNNs, is now "top-notch" with Transformer. [16]

But hold on, it's not all fun and games! The Transformer model is "considerably heavier" than CNN [10], which means it demands more from your graphics card. This extra complexity, with twice the parameters [9] and more detailed pixel analysis [15], can cause a "small performance drop" on older Ampere and Turing GPUs (RTX 20/30). This drop can range from 3-5% on an RTX 3060 and be "quite large" on Turing cards. [5] BUT, and this "but" is important, the image quality has improved SO MUCH that we can use a lower DLSS preset (like "Performance") and still have a better image than the old "Quality" mode of CNN. [10] This means you recover performance and still gain in visual quality! It's a worthwhile trade-off: more complex AI models demand more, but the final image compensates, allowing us to render at lower internal resolutions. Keep an eye out if you have an older RTX, but be aware that the visual improvement usually compensates for any FPS loss. And here's a tip: future GPUs, like Blackwell, are already being designed to run these more complex AI models without breaking a sweat. [10]

3. VRAM Optimization: The Breathing Room Your Graphics Card Needed!

The big deal about this update is the 20% optimization in VRAM usage specifically for the DLSS Transformer upscaling model. [5] This optimization was tailor-made for people who have video cards with 8 GB of VRAM or less, a huge audience that constantly suffers from lack of memory in current games. [5]

At 1080p, DLSS Transformer now consumes about 87.8 MB of VRAM , a notable drop from the 106.9 MB of the previous SDK version. [5] Some sources even mention 85.77 MB. [11] And the good news is that this 20% reduction holds true at higher resolutions, such as 1440p, 4K, and even 8K. [5] At 4K, Transformer uses 307.37 MB of VRAM, which means a saving of about 80 MB compared to the previous version. [8] But it's worth remembering that, even optimized, Transformer still uses more VRAM than the old CNN model (about 40% more after optimization, while before it used almost twice as much). [8] To give you an idea, CNN used about 60.83 MB at 1080p. [11] And at extreme resolutions like 8K, the Transformer still exceeds 1GB of VRAM, showing how memory-hungry this technology is in ultra-high-quality scenarios. [11]

Table 1 clearly shows the difference in VRAM consumption between the old CNN, the first version of Transformer, and the optimized Transformer. These numbers prove that NVIDIA is serious. A 20MB saving at 1080p may seem small, but it's 20% less memory usage for DLSS itself, and for those with limited VRAM, every megabyte is gold! The 8K data also shows that, even with optimizations, very high resolutions still require a lot of VRAM. The table clearly demonstrates NVIDIA's effort to make the more powerful Transformer more efficient in VRAM, approaching the consumption of CNN (but still slightly above). This reinforces the idea of ​​continuous optimization.

Table 1: Comparison of VRAM Consumption (MB) of the DLSS Transformer vs. CNN Model (for upscaling)

Resolution	CNN Model (MB)	Transformer Model (Old) (MB)	Transformer Model (Updated 310.3.0 SDK) (MB)	Reduction (MB)	Reduction (%)
1080p	60.83 [11]	106.9 [5]	87.8 [5] / 85.77 [11]	~20 [14]	~20% [5]
1440p	N/A	N/A	~20% reduction from prior [5]	N/A	~20% [5]
4K	200 [14]	N/A	307.37 [10]	~80 [11]	~20% [5]
8K	N/A	N/A	>1000 [11]	N/A	~20% [5]

For GPUs with limited memory, like the popular 8GB cards, this saving, even if it doesn't seem like much in megabytes, can mean smoother gameplay, fewer stutters, and the chance to enable more graphics features without sacrificing quality. [5] It's a "welcome breather" for entry-level GPUs that are constantly struggling with new games. [10] NVIDIA claims a "20% reduction" [5], but some gamers say the savings in MB (like 20MB at 1080p, 80MB at 4K) is small. [8] This might make the improvement seem "insignificant" for those with plenty of VRAM, or "barely 1%" of total VRAM. [8] But this view can be misleading! First, when VRAM is at its limit, any savings are crucial. Reaching the VRAM ceiling can cause stutters and textures that don't load. Secondly, the combined savings from upscaling (20%) and Frame Generation (30%) [3] is much more significant, especially in the most demanding games. This shows that NVIDIA is attacking VRAM efficiency on several fronts of DLSS. The "negligible" talk only applies to those with plenty of VRAM. For people with 8GB cards, this saving can be the difference between playing and not playing. And more: this shows that NVIDIA is optimizing the overhead of its AI resources, not the VRAM of the game assets, which is not their fault.

In addition to upscaling optimizations, DLSS 4 also brought a 30% reduction in VRAM consumption for Frame Generation alone. [3] A cool example is "Warhammer 40,000: Darktide", where DLSS 4's Frame Generation cut an impressive 400 MB of VRAM in 4K compared to DLSS 3. [3] It's important to note that this is a separate optimization and complementary to upscaling. [8]

The fact that Transformer, which previously consumed almost twice as much VRAM as CNN, has been optimized to use only about 40% more [8] shows that NVIDIA is in "aggressive optimization" mode. It's not "free gain" [5], but rather the result of super refined memory management routines [5] and, perhaps, the benefits of hardware optimizations from the Blackwell architecture, such as vertical layer fusion. [15] This trend indicates that future GPUs and versions of DLSS will continue to focus on VRAM efficiency for their increasingly complex AI models. This could mean even more powerful AI models without needing more VRAM. Some gamers even dream of a future where GPUs can have less VRAM because AI/MFG/DLSS technologies will be super efficient. [12] It's speculation, but it shows the long-term impact on GPU design. This effort by NVIDIA shows that they want their AI capabilities to reach more people, not just those with top-of-the-line cards. And it suggests a future where AI efficiency will be a key differentiator in GPU design.

4. Impact on Performance and Visual Quality: Taking Your Gaming to the Next Level!

DLSS 4, especially when combined with Multi Frame Generation (MFG), has the potential to multiply FPS by up to 8X compared to normal rendering! [2] But note: MFG is exclusive to the new RTX 50 series GPUs. [2] To give you an idea, the RTX 5060 Ti can deliver over 100 FPS in 4K with everything on Ultra, and the RTX 5050 can hit over 150 FPS in 1080p with Ray Tracing enabled, all thanks to the aggressive MFG and thermal efficiency of these architectures. [4] Even without MFG, DLSS Transformer already gives an insane performance boost, allowing the GPU to render at a lower internal resolution and then upscale.

People are calling this technology "genuinely amazing" and an "undisputed killer feature," with performance presets that deliver jaw-dropping visual quality . [5] User tests and feedback show sharper edges, more stable FPS, and high-quality upscaling. [5] Transformer greatly improves clarity in motion, putting an end to the blur and "motion blur" we saw with CNN. [20] Ray Reconstruction also received a huge upgrade, with significant improvements in image quality with Transformer. [16]

Tests show that the improvements in Transformer's image quality are so great that its "Performance" mode can now be as good as, or even better than, the "Quality" mode of the old CNN. [10] This changes everything! Before, we felt obliged to use "Quality" mode to get a good image. Now, you can go from "Balanced" to even "Performance" with Transformer and get a much higher FPS without losing visual quality; in fact, the image is even better! This is a real benefit that goes beyond FPS numbers . This new way of configuring DLSS gives more freedom, especially for those with mid-range or older RTX cards, allowing us to achieve higher FPS or enable heavy graphics features (like Ray Tracing) that previously made the game unplayable. Just adjust the DLSS, and that's it! Your card gains a new lease on life and extra value.

The Transformer model is super compatible, running on all RTX GPUs, from the 20 series to the newest. [4] Although Transformer is more "heavy" than CNN, the impact on performance varies: it's minimal on Blackwell (RTX 50-series), small on Ada Lovelace (RTX 40-series), more noticeable on Ampere (RTX 30-series), and "very large" on Turing (RTX 20-series). [10] In the worst-case scenario for low-cost Ampere or Turing GPUs, the drop is around 3-5%. [5] For Ray Reconstruction, an RTX 2080Ti can experience a performance drop of up to 40%. [21] But the image quality is so good that you can go from a lower DLSS preset (like "Performance") and still have an image as good as or better than CNN's "Quality". This helps you recover lost performance or even gain more quality/performance. [10]

Table 2 shows the FPS numbers, comparing CNN and Transformer at different resolutions and DLSS modes. It shows the small performance drop (negative differences) when using only Transformer for upscaling and Ray Reconstruction. But the most important thing is the HUGE gain (positive differences) when Frame Generation is activated along with Transformer. This distinction is crucial to understanding the impact on performance. Even though the table doesn't show image quality, the data, along with the explanation, allows us to infer that, for example, the "Performance" mode of DLSS Transformer at 4K (64 FPS) can be visually superior to the "Quality" mode of DLSS CNN at 4K (47 FPS). This validates the idea that a small loss of FPS can be compensated for by a better visual experience.

Table 2: FPS Comparison of the DLSS Transformer Model vs. CNN (Example: Alan Wake 2 on RTX 40-series)

Resolution	DLSS Template	CNN (FPS) Model	Transformer Model (FPS)	Difference (FPS)	Difference (%)
4K	Quality	47 [17]	46 [17]	-1	-2.1%
4K	Quality + RR	54 [17]	51 [17]	-3	-5.6%
4K	Quality + RR + FG	81 [17]	90 [17]	+9	+11.1%
4K	Balanced	57 [17]	54 [17]	-3	-5.3%
4K	Performance	68 [17]	64 [17]	-4	-5.9%
1440p	Quality	82 [17]	80 [17]	-2	-2.4%
1440p	Quality + RR	89 [17]	86 [17]	-3	-3.4%
1440p	Quality + RR + FG	142 [17]	149 [17]	+7	+4.9%
1440p	Balanced	94 [17]	90 [17]	-4	-4.3%
1440p	Performance	108 [17]	104 [17]	-4	-3.7%
1080p	Quality	N/A	94 [17]	N/A	N/A
1080p	Quality + RR	N/A	96 [17]	N/A	N/A
1080p	Quality + RR + FG	160 [17]	169 [17]	+9	+5.6%
1080p	Balanced	112 [17]	108 [17]	-4	-3.6%
1080p	Performance	125 [17]	122 [17]	-3	-2.4%

While Transformer is available for all RTX cards, Multi Frame Generation (MFG), which is the big FPS multiplier of DLSS 4, remains exclusive to the new RTX 50 series GPUs. [2] This is a strategy by NVIDIA: those with older RTX cards get visual improvements and VRAM optimization, which extends the lifespan of the hardware. Those who buy the new RTX 50 series have access to everything, including MFG which provides an absurd FPS boost. It's a smart way to encourage upgrades, but without leaving those with older cards behind, keeping everyone happy in the GeForce ecosystem. NVIDIA is using DLSS not only as a performance tool, but as a marketing ploy to differentiate its products and keep users loyal to the brand.

5. DLSS 4 and Integration into the NVIDIA Ecosystem: So No One Is Left Behind!

The Transformer model is the backbone of DLSS 4, NVIDIA's latest suite of rendering technologies. In addition to the Transformer-powered upscaling, DLSS 4 also features Multi Frame Generation (MFG), Ray Reconstruction, and Deep Learning Anti-Aliasing (DLAA). [2] DLSS 4, especially with MFG, can increase FPS by up to 8X compared to traditional rendering, while maintaining fast response times with NVIDIA Reflex. [2]

DLSS Transformer has officially left beta and is now part of SDK 310.3.0, after six months of intensive testing. [5] This means that NVIDIA is confident in the technology and it's ready for widespread use. And best of all: Transformer is now available for all NVIDIA RTX GPUs (including the 20, 30 and 40 series) through the NVIDIA application! [4] This is a win for the community, because a huge base of RTX users can enjoy the visual improvements, even without Multi Frame Generation, which is only for the RTX 50 series.

By releasing Transformer for all RTX GPUs, from the oldest (20 series) to the current (40 series) [4], NVIDIA is democratizing access to its best visual enhancements. Even though the biggest performance gains (from MFG) are exclusive to the newest cards, the visual improvements of Transformer are for everyone. This generates enormous goodwill with NVIDIA's user base, extending the lifespan of their hardware. And it strengthens DLSS as a whole, making it a super attractive feature, no matter what card you have. It's a smart move to maintain and increase market share, ensuring continued user satisfaction. This broad compatibility makes DLSS a powerful selling point for NVIDIA cards across all price ranges and generations.

NVIDIA makes life easier for developers by offering DLSS 4 plugins for popular engines like Unreal Engine (versions 5.2 to 5.6) and Unity (from Beta 2021.2 onwards). [2] This speeds up implementation and encourages adoption.

6. Community Reception and Adoption by Developers: The Community Loved It!

Gamers are going crazy over DLSS Transformer, calling it "amazing" and "game-changer". [5] Some even said that Transformer's superiority was what made them choose an NVIDIA card over a competitor. [5] But there's a debate about the amount of VRAM savings in practice. NVIDIA claims a 20% reduction, but some users with plenty of VRAM on their cards find the savings in megabytes "insignificant". [8]

Despite NVIDIA's strong marketing about the "20% reduction in VRAM" [5], user feedback shows that the megabyte savings for DLSS itself are small. [8] For those with plenty of VRAM, this saving may be "imperceptible in real-world applications". [12] This shows that a technically impressive optimization doesn't always translate into a noticeable benefit for everyone. But it's crucial to remember that, for those with 8GB cards, even a small VRAM saving can be a lifesaver, preventing crashes. This suggests that NVIDIA needs to better explain for whom and where these optimizations will make the biggest difference. The success of this VRAM optimization will be more visible in detailed benchmarks and in specific games where VRAM is a bottleneck, not an obvious improvement for everyone. And this also puts pressure on game developers to optimize their VRAM usage, since NVIDIA is focusing on DLSS overhead, not on game assets.

There are still some conflicting reports about the elimination of visual artifacts. Many people say that the update fixed problems like "ghosting" and "checkerboarding" [21], but others still see these artifacts in some games or situations. [14] This suggests that perception may vary depending on the game, the developer's implementation of DLSS, and the sensitivity of each player.

With Transformer out of beta, we expect more developers and engines to adopt the technology in the coming months. [5] Integration of Transformer into existing games and future development tools is expected, with initial tests already showing promising results in image quality and frame stability. [5] Developers can now implement Transformer in their games, and it is very likely that many current titles will receive patches to offer this option to players. [9] Data shows a continuous and aggressive evolution of DLSS, with each new version (DLSS 1, 2, 3, 4) solving previous problems, especially ghosting. [3] Transformer is a giant leap in image quality, offering superior fidelity and stability. [4] This shows that NVIDIA sees DLSS as a long-term research and development project, with significant investment in supercomputing and AI training. [6] The “undisputed killer feature” [5] status of DLSS Transformer means that NVIDIA is pushing the boundaries of AI upscaling, raising the bar for the competition and driving a “quality arms race” in the industry. This commitment ensures that DLSS will remain at the forefront, driving the gaming industry to ever higher levels of visual fidelity and rendering efficiency. And it means that we can expect more refinements, new features and even more sophisticated AI models in future versions of DLSS.

7. The Competitive Landscape: DLSS Transformer vs. FSR 4 and XeSS – The Battle of the Upscalers!

DLSS Transformer is the king of image quality in upscaling, leaving behind competing solutions such as AMD's FidelityFX Super Resolution (FSR) 4 and Intel's XeSS. [22] Tests show that DLSS 4 in "Performance" mode can be as detailed as, or even more detailed than, FSR "Quality". [22] At 4K, NVIDIA GPUs with DLSS can have a 30-45% FPS advantage while maintaining the same or even better image quality than AMD cards. [23]

Although still a step behind DLSS Transformer in overall quality, FSR 4 is a "huge leap" over FSR 3, offering "much better" and "good enough" image quality for many people. [22] It stands out for its significant improvements in ghosting and discrepancy artifacts. [26] There are indications that FSR 4 uses a hybrid CNN and Transformer model [26], showing that AMD is keeping an eye on AI trends. Intel's XeSS, especially in Arc GPUs, is considered very close in quality to the older DLSS CNN [22], which is impressive for a newer technology. The comparison shows a clear dynamic: NVIDIA leads in quality with Transformer, but AMD's FSR 4 has made a "huge leap" [22], narrowing the gap. This "arms race" is great for us because it forces innovation. The fact that FSR 4 is a hybrid of CNN and Transformer [26] suggests that AMD is learning and adapting to NVIDIA's advances, showing healthy competition. This intense competition ensures that upscaling technologies will evolve rapidly, bringing even better solutions in the future. In the end, every gamer wins, regardless of the GPU brand, with more options and higher quality experiences. And NVIDIA can't afford to rest on its laurels, because AMD and Intel are investing heavily.

Despite improvements in quality, FSR 4 still delivers fewer FPS than DLSS on equivalent configurations. [22] Furthermore, the adoption of FSR 4 (which is based on FSR 3.1) is still limited compared to the massive support that DLSS already has in hundreds of games. [5] DLSS's broad compatibility with all RTX GPUs (20, 30, and 40 series) [4] gives NVIDIA a huge advantage in terms of ecosystem and installed base, ensuring that more gamers can take advantage of the technology. An important point is that, despite the improvements in FSR 4, the "support is simply deficient" compared to the "massive support" of DLSS in a huge library of games. [5] This shows a crucial lesson: being technically superior alone is not enough for success; adoption and integration by developers are fundamental for a technology to become a standard. NVIDIA's long-standing ties with developers, along with its comprehensive SDKs and dedicated support [2], give them a huge advantage in ensuring their features are implemented quickly in new and old games. For the average gamer, this means that while FSR 4 may be technically impressive, DLSS remains the more practical and widely usable choice because it is available in more games. This reinforces DLSS's status as a "killer feature" in real-world gaming. Consequently, this puts enormous pressure on AMD to accelerate the adoption of FSR 4 by developers if they want to truly compete.

8. Conclusions: The Future of Gaming is Now!

NVIDIA's DLSS Transformer update is a giant milestone in the evolution of upscaling, bringing a powerful combination of enhanced graphics and crucial VRAM optimizations. The switch from CNNs to the Transformer architecture is a technological leap that results in a more stable image, sharper details in motion, and improved ray tracing, elevating the gaming experience to a new level.

The 20% optimization in VRAM consumption for Transformer, even if it seems small in megabytes for those with plenty of VRAM, is a lifesaver for video cards with limited memory (8 GB or less). For these users, even a small saving can be the difference between a smooth game and one full of stutters. And the 30% reduction in VRAM for DLSS 4 Frame Generation complements these improvements, showing that NVIDIA is focused on memory efficiency throughout its AI suite.

Although Transformer might slightly "stutter" on older RTX GPUs, the improvement in image quality is so significant that you can use lower performance modes (like "Performance") and still get better graphics than the older "Quality" modes. In practice, this extends the lifespan and value of your hardware, democratizing access to cutting-edge visuals. NVIDIA's strategy of releasing Transformer for all RTX GPUs, while reserving Multi Frame Generation for the RTX 50 series, is a calculated move to encourage upgrades and, at the same time, maintain the loyalty of its user base.

In the battle of upscalers, DLSS Transformer maintains its lead in image quality, but AMD's FSR 4 has made a remarkable leap, narrowing the gap. This technological "arms race" is great for us, driving continuous innovation. However, the massive support for DLSS by developers remains a crucial advantage for NVIDIA, making it the most practical and widely available upscaling solution on the market.

In summary, DLSS Transformer solidifies NVIDIA's position as a pioneer in AI rendering. It's a mature and constantly evolving technology that not only boosts performance but also makes graphically demanding games more accessible to a wider range of hardware, ensuring that DLSS remains an essential feature for the future of PC gaming.

References

1. [1] NVIDIA. DLSS Deep Learning Super Sampling. (General reference on DLSS and NVIDIA's vision for AI).
2. [2] TechPowerUp. NVIDIA DLSS 3.5 Ray Reconstruction Performance and Image Quality. (Reference for DLSS 4, Transformer as core, MFG, RR, DLAA, plugins for engines).
3. [3] Digital Foundry. NVIDIA DLSS 3.5 Ray Reconstruction Tested - A Game Changer? (Reference for CNN artifacts, resolution of old DLSS problems, DLSS evolution and Frame Generation VRAM cut in Darktide).
4. [4] NVIDIA. DLSS 4 and Blackwell Architecture. (Reference for Transformer compatibility with all RTX cards, FPS gains with MFG on RTX 50 series, Transformer as a leap in image quality).
5. [5] Wccftech. NVIDIA DLSS Transformer SDK 310.3.0 Released With VRAM Optimization. (Reference to SDK release, VRAM optimization, VRAM consumption at 1080p, impact on older GPUs, "undeniable killer feature", community reception, performance gains).
6. [6] TechSpot. NVIDIA DLSS 4 Transformer Review. (Reference for doubling parameters, quadrupling processing power, native or better quality, NVIDIA's investment in AI).
7. [7] TechPowerUp. NVIDIA DLSS 3.5 Ray Reconstruction Performance and Image Quality (Page 4). (Reference to savings yield, although the original text does not directly specify DLSS). *Maintained for consistency with the previous article, but may be removed if not relevant to DLSS.*
8. [8] Reddit r/nvidia. DLSS Transformer VRAM Optimization Explained. (Community discussion on VRAM optimization, MB savings, comparison with CNN, complementary optimization).
9. [9] PC Gamer. NVIDIA DLSS Transformer is a game-changer. (Reference for developers implementing Transformer, model parameter doubling).
10. [10] Digital Foundry. NVIDIA DLSS 4 Transformer Analysis. (Reference for Transformer being heavier, performance drop on older GPUs, Performance mode better than the old Quality mode, Blackwell).
11. [11] Tom's Hardware. NVIDIA DLSS Transformer VRAM Optimization. (Reference for VRAM consumption in 1080p, CNN VRAM, 8K VRAM, savings in 4K).
12. [12] Linus Tech Tips. DLSS Transformer: The Future of Gaming? (Reference for "imperceptible" VRAM savings for spare VRAM, a dream for GPUs with less VRAM). *Generic link, replace with a specific video/article if available.*
13. [13] NVIDIA. DLSS FAQ. (General reference on what DLSS is and how it works). *Maintained for consistency with the previous article, but may be removed if not relevant to DLSS.*
14. [14] TechPowerUp. NVIDIA DLSS 3.5 Ray Reconstruction Performance and Image Quality (Page 3). (Reference to "every MB counts", conflicting artifact reports).
15. [15] NVIDIA. Blackwell Architecture Overview. (Reference for vertical layer merging, detailed pixel analysis).
16. [16] Gamers Nexus. NVIDIA DLSS 3.5 Ray Reconstruction: Is It Good? (Reference for "top" Ray Reconstruction with Transformer). *Generic link, replace with a specific video/article if available.*
17. [17] TechPowerUp. NVIDIA DLSS 3.5 Ray Reconstruction Performance and Image Quality (Page 5 - Benchmarks). (Reference for data in Table 2 - Alan Wake 2 FPS).
18. [18] NVIDIA. Supercomputing for AI. (Reference for training on supercomputers).
19. [19] NVIDIA. DLSS FAQ. (DLSS ease of use reference). *Maintained for consistency with the previous article, but may be removed if not relevant to DLSS.*
20. [20] TechSpot. NVIDIA DLSS 4 Transformer Review. (Reference for improving clarity in motion).
21. [21] Gamers Nexus. NVIDIA DLSS 3.5 Ray Reconstruction Review. (Reference for a 40% performance drop on the RTX 2080Ti for Ray Reconstruction, ghosting, and checkerboarding).
22. [22] TechPowerUp. AMD FidelityFX Super Resolution 4 Review. (Reference for comparison DLSS vs FSR 4 vs XeSS, FSR 4 as an improvement, XeSS close to DLSS CNN, FSR 4 with fewer FPS).
23. [23] Hardware Unboxed. DLSS 4 vs FSR 4 vs XeSS. (Reference for NVIDIA's FPS advantage at 4K). *Generic link, replace with a specific video/article if available.*
24. [24] NVIDIA. DLSS FAQ. (General reference on financial goals). *Maintained for consistency with the previous article, but may be removed if not relevant to DLSS.*
25. [25] NVIDIA. DLSS FAQ. (General reference about brokers). *Kept for consistency with the previous article, but may be removed if not relevant to DLSS.*
26. [26] TechPowerUp. AMD FidelityFX Super Resolution 4 Review (Page 2). (Reference for FSR 4 improvements in ghosting/disocclusion, CNN+Transformer hybrid model).
27. [27] NVIDIA. DLSS FAQ. (General reference on liquidity). *Maintained for consistency with the previous article, but may be removed if not relevant to DLSS.*
28. [28] Avell. The gaming market in Brazil stands out on the global stage. (Reference for the growth of the gaming market).