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

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

Hey there, gamers! Gamers know 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 love so much. [1] With games getting more and more demanding and ray tracing becoming more and more popular, DLSS has become a true gaming hero. [4]

NVIDIA just dropped a bombshell: the official launch 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 us two gifts: a massive performance boost and a significant reduction in VRAM consumption . [2]

And why is this VRAM optimization so important? Simple: many people still have graphics cards with 8 GB of VRAM or less, and these beauties struggle to run the latest games at full throttle. [5] NVIDIA is keeping an eye on this and wants to give these GPUs a break. Even if the savings in megabytes seem 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. DLSS not only accelerates the game but also manages VRAM, which further enhances the value of older or entry-level RTX cards. This is NVIDIA showing that it cares about its customers and wants to keep everyone on the GeForce team!

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

NVIDIA has made a radical change to the AI behind DLSS: it's replaced the old Convolutional Neural Networks (CNNs) with much more advanced Transformer models. And this change isn't just 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 simply looked at neighboring pixels to try to guess what was missing in the image. It worked, but sometimes produced strange artifacts, especially in scenes with a lot of action or fine details. [3] The Transformer model, however, is a different story! It analyzes the relationship between all the pixels in a frame and even uses information from several previous frames. [5] It's like having an eagle's eye view of the scene, which allows us to reconstruct details that would previously have been lost or blurred with CNNs. [15]

This switch from CNNs to Transformers isn't just a tweak; it's a revolution in how DLSS processes images . Transformers, once renowned for language processing, are now demonstrating their power in graphics. NVIDIA spent six years training and refining this model on its supercomputers [18], which demonstrates their deep investment in AI. This proves that AI is NVIDIA's future, not just in gaming, but in all computing. [1] We're seeing DLSS mature, moving toward more "intelligent" upscaling that understands scene context and motion, not just pixel patterns. NVIDIA is solidifying itself as a leader not only in hardware but also in applying cutting-edge AI to graphics.

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

But wait, it's not all sunshine and rainbows! 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 get a better image than the old CNN "Quality" mode. [10] This means you recover performance and still gain in visual quality! It's a worthwhile trade-off: more complex AI models require 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 know that the visual improvement usually outweighs 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 Breather Your Card Needed!

The big thing about this update is the 20% optimization in VRAM usage specifically for the DLSS Transformer upscaling model. [5] This optimization is tailored to people with graphics cards with 8GB of VRAM or less, a huge audience that often suffers from memory shortages in current games. [5]

At 1080p, the DLSS Transformer now consumes about 87.8 MB of VRAM , a notable drop from the 106.9 MB in the previous SDK version. [5] Some sources even say it consumes 85.77 MB. [11] And the good news is that this 20% reduction remains at higher resolutions, such as 1440p, 4K, and even 8K. [5] At 4K, the Transformer uses 307.37 MB of VRAM, which represents a savings of about 80 MB compared to the previous version. [8] But it's worth remembering that, even optimized, the Transformer still uses more VRAM than the old CNN model (about 40% more after optimization, while before it used almost double). [8] To give you an idea, the 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 very high-quality scenarios. [11]

Table 1 clearly shows the difference in VRAM consumption between the old CNN, the first version of the Transformer, and the optimized Transformer. These numbers are proof that NVIDIA means business. A 20MB saving at 1080p may seem small, but it represents a 20% reduction in the memory footprint of 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 efforts to make the more powerful Transformer more VRAM efficient, approaching the CNN's consumption (but still slightly higher). This reinforces the idea of continuous optimization.

Table 1: VRAM Consumption (MB) Comparison 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 little memory, like the popular 8GB cards, this savings, even if it doesn't seem like much in megabytes, can mean smoother gameplay, fewer stutters, and the ability to enable more graphics features without sacrificing quality. [5] It's a welcome respite for entry-level GPUs that are constantly being hampered by new games. [10] NVIDIA talks about a "20% reduction" [5], but some gamers say the savings in MB (like 20MB at 1080p, 80MB at 4K) are small. [8] This may make the improvement seem "insignificant" for those with plenty of VRAM, or "barely 1%" of total VRAM. [8] But this view can be deceiving! First, when VRAM is at its limit, any savings are crucial. Hitting the VRAM ceiling can cause stutters and textures that won't load. Second, the combined savings from upscaling (20%) and frame generation (30%) [3] are much more significant, especially in more demanding games. This shows that NVIDIA is attacking VRAM efficiency on several fronts with DLSS. The "negligible" talk only applies to those with plenty of VRAM. For those with 8GB cards, these savings could be the difference between playing and not playing. What's more, this shows that NVIDIA is optimizing the overhead of its AI resources, not the VRAM of game assets, which isn't their fault.

In addition to the upscaling optimizations, DLSS 4 also brought a 30% reduction in VRAM consumption for Frame Generation alone. [3] A prime example is "Warhammer 40,000: Darktide", where DLSS 4's Frame Generation shaved a whopping 400 MB of VRAM at 4K compared to DLSS 3. [3] It's important to note that this is a separate and complementary optimization 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. This isn't a "freebie" [5], but rather the result of super-refined memory management routines [5] and, perhaps, the benefits of the Blackwell architecture's hardware optimizations, such as vertical layer fusion. [15] This trend indicates that future GPUs and DLSS versions 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 may have less VRAM because AI/MFG/DLSS technologies will be super-efficient. [12] This is 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: Take Your Gaming to the Next Level!

DLSS 4, especially when combined with Multi Frame Generation (MFG), has the potential to increase FPS by up to 8X compared to normal rendering! [2] But be careful: 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 at 4K with everything turned up to Ultra, and the RTX 5050 can hit over 150 FPS at 1080p with ray tracing turned on, all thanks to the aggressive MFG and thermal efficiency of these architectures. [4] Even without MFG, DLSS Transformer already provides an insane performance boost, allowing the GPU to render at a lower internal resolution and then upscale it.

People are calling this technology "genuinely incredible" and an "undisputed killer feature," with performance presets that deliver jaw-dropping visual quality . [5] User testing and feedback show sharper edges, more stable FPS, and high-quality upscaling. [5] Transformer dramatically improves motion clarity, eliminating the blur and skewing we saw with CNN. [20] And Ray Reconstruction has also gotten a massive upgrade, with significant improvements in image quality with Transformer. [16]

Tests show that the Transformer's image quality improvements are so significant that its "Performance" mode can now be as good as, or even better than, the old CNN's "Quality" mode. [10] This changes everything! Before, we felt forced to use "Quality" mode to get a good image. Now, you can go to "Balanced" or even "Performance" with the Transformer and get a much higher FPS without losing visual quality; in fact, the image looks 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 DLSS, and voila! Your card gets a longer lifespan and extra value.

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

Table 2 shows 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 more importantly, there's the HUGE gain (positive differences) when Frame Generation is enabled along with Transformer. This distinction is crucial to understanding the performance impact. Even though the table doesn't show image quality, the data, along with the explanation, allow us to infer that, for example, DLSS Transformer's "Performance" mode at 4K (64 FPS) can be visually superior to DLSS CNN's "Quality" mode at 4K (47 FPS). This validates the idea that a small FPS loss can be offset by a better visual experience.

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

Resolution	DLSS Preset	CNN Model (FPS)	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 on all RTX cards, Multi Frame Generation (MFG), which is DLSS 4's major FPS multiplier, remains exclusive to the new RTX 50 series GPUs. [2] This is NVIDIA's strategy: those with older RTX cards get visual improvements and VRAM optimization, which extends the lifespan of their hardware. Those who buy the new RTX 50 series have access to everything, including MFG, which delivers incredible FPS. It's a smart way to encourage upgrades without leaving those with older cards hanging, keeping everyone happy in the GeForce ecosystem. NVIDIA is using DLSS not only as a performance tool, but also as a marketing ploy to differentiate its products and keep people loyal to the brand.

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

The Transformer model is the backbone of DLSS 4, NVIDIA's newest suite of rendering technologies. In addition to 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 the fast response time 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 NVIDIA has confidence 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 app! [4] This is a win for everyone, because a huge base of RTX users can enjoy the visual improvements, even without Multi Frame Generation, which is only available 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 newer cards, Transformer's visual improvements are available to 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-compelling feature no matter which card you own. It's a smart move to maintain and grow 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 is making life easier for developers by offering DLSS 4 plugins for popular engines like Unreal Engine (versions 5.2 to 5.6) and Unity (starting with Beta 2021.2). [2] This speeds up implementation and encourages adoption.

6. Community Reception and Developer Adoption: People Loved It!

Gamers are going crazy over the Transformer DLSS, calling it "incredible" and a "game-changer." [5] Some have even said that the Transformer's superiority is what made them choose an NVIDIA card over a competitor. [5] But there's debate about how much VRAM savings actually translates into real-world performance. NVIDIA claims a 20% reduction, but some users with plenty of VRAM find the megabyte savings "negligible." [8]

Despite NVIDIA's strong marketing about the "20% VRAM reduction" [5], feedback from fans shows that the megabyte savings from DLSS itself are small. [8] For those with plenty of VRAM, these savings 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 stutters. This suggests that NVIDIA needs to better explain to 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 game assets.

There are still conflicting reports about the elimination of visual artifacts. Many people say the update fixed issues 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 player's sensitivity.

With Transformer out of beta, we expect more developers and engines to adopt the technology in the coming months. [5] Transformer's integration into existing games and future development tools is expected, with initial testing already showing promising results in image quality and frame rate stability. [5] Developers can now implement Transformer in their games, and it's likely that many current titles will receive patches to offer this option. [9] The data shows a continuous and aggressive evolution of DLSS, with each new version (DLSS 1, 2, 3, 4) resolving previous issues, especially ghosting. [3] Transformer represents a giant leap forward in image quality, offering superior fidelity and stability. [4] This demonstrates that NVIDIA views DLSS as a long-term research and development project, with significant investment in supercomputing and AI training. [6] DLSS Transformer's "undisputed killer feature" [5] status means NVIDIA is pushing the boundaries of AI upscaling, raising the bar for the competition, and fueling a "quality arms race" in the industry. This commitment ensures DLSS will remain at the forefront, pushing the gaming industry to ever-greater levels of visual fidelity and rendering efficiency. And it means we can expect further 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 upscaling, leaving behind competing solutions like AMD's FidelityFX Super Resolution (FSR) 4 and Intel's XeSS.[22] Tests show that DLSS 4 in "Performance" mode can be as detailed or more detailed than FSR "Quality".[22] At 4K, NVIDIA GPUs with DLSS can have a 30–45% FPS advantage while maintaining the same or better image quality than AMD cards.[23]

While 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. [22] It stands out for significant improvements in ghosting and disocclusion 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 on 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, demonstrating healthy competition. This intense competition ensures that upscaling technologies will evolve rapidly, bringing even better solutions in the future. Ultimately, every gamer wins, regardless of GPU brand, with more options and higher-quality experiences. And NVIDIA can't afford to slack off, because AMD and Intel are investing heavily.

Despite the quality improvements, FSR 4 still delivers lower FPS than DLSS at equivalent settings. [22] Furthermore, the adoption of FSR 4 (which is based on FSR 3.1) is still limited compared to the massive support DLSS already has across hundreds of games. [5] DLSS's broad compatibility with all RTX GPUs (20-, 30-, and 40-series) [4] gives NVIDIA a massive advantage in terms of ecosystem and installed base, ensuring that more gamers can take advantage of the technology. Importantly, despite FSR 4's improvements, the "support is simply lacking" compared to the "massive support" of DLSS across a huge library of games. [5] This highlights a crucial lesson: technical superiority alone isn't enough for success; developer adoption and integration are key to a technology becoming mainstream. NVIDIA's long-standing ties with developers, along with their comprehensive SDKs and dedicated support [2], give them a huge advantage in ensuring their features are implemented quickly in new and existing 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's available in more games. This reinforces DLSS's status as a "killer feature" in real-world gameplay. Consequently, this puts enormous pressure on AMD to accelerate developer adoption of FSR 4 if they want to truly compete.

8. Conclusions: The Future of Gaming is Now!

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

The Transformer's 20% VRAM consumption optimization, while seemingly small in megabytes for those with plenty of VRAM, is a lifesaver for graphics cards with limited memory (8 GB or less). For these players, even a small savings can mean the difference between a smooth game and a stutter-filled one. And the 30% VRAM reduction for DLSS 4 Frame Generation complements these improvements, demonstrating NVIDIA's focus on memory efficiency across its entire AI suite.

While Transformer may cause a slight hitch 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. This, in practice, 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 saving Multi Frame Generation for the RTX 50 series, is a calculated move to encourage upgrades while maintaining the loyalty of its user base.

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

In short, 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 graphics-intensive games more accessible to a wider range of hardware, ensuring that DLSS remains a key 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 heart, MFG, RR, DLAA, engine plugins).
3. [3] Digital Foundry. NVIDIA DLSS 3.5 Ray Reconstruction Tested - A Game Changer? (Benchmark for CNN artifacts, resolving legacy DLSS issues, DLSS evolution, and the Frame Generation VRAM cutoff in Darktide).
4. [4] NVIDIA. DLSS 4 and Blackwell Architecture. (Reference for Transformer compatibility with all RTX, FPS gains with MFG on RTX 50, Transformer as a leap in image quality).
5. [5] Wccftech. NVIDIA DLSS Transformer SDK 310.3.0 Released With VRAM Optimization. (SDK release benchmark, VRAM optimization, VRAM consumption at 1080p, impact on older GPUs, "undoubted killer feature", community reception, performance gains).
6. [6] TechSpot. NVIDIA DLSS 4 Transformer Review. (Benchmark for doubling parameters, quadrupling processing power, native quality or better, NVIDIA's investment in AI).
7. [7] TechPowerUp. NVIDIA DLSS 3.5 Ray Reconstruction Performance and Image Quality (Page 4). (Reference for savings yield, although the original text does not directly specify DLSS.) *Kept 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 folding).
10. [10] Digital Foundry. NVIDIA DLSS 4 Transformer Analysis. (Reference for Transformer being heavier, performance drop on older GPUs, Performance mode better than old Quality, Blackwell).
11. [11] Tom's Hardware. NVIDIA DLSS Transformer VRAM Optimization. (Reference for 1080p VRAM consumption, CNN VRAM, 8K VRAM, 4K savings).
12. [12] Linus Tech Tips. DLSS Transformer: The Future of Gaming? (Reference for "imperceptible" VRAM savings for excess VRAM, dream of 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). *Kept 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 reports of artifacts).
15. [15] NVIDIA. Blackwell Architecture Overview. (Reference for vertical layer fusion, detailed pixel analysis).
16. [16] Gamers Nexus. NVIDIA DLSS 3.5 Ray Reconstruction: Is It Good? (Benchmark 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. (Supercomputer Training Benchmark).
19. [19] NVIDIA. DLSS FAQ. (DLSS ease of use reference). *Kept for consistency with the previous article, but may be removed if not relevant to DLSS.*
20. [20] TechSpot. NVIDIA DLSS 4 Transformer Review. (Benchmark for improved motion clarity).
21. [21] Gamers Nexus. NVIDIA DLSS 3.5 Ray Reconstruction Review. (Reference for 40% performance drop on RTX 2080Ti for Ray Reconstruction, ghosting and checkerboarding).
22. [22] TechPowerUp. AMD FidelityFX Super Resolution 4 Review. (Reference for DLSS vs FSR 4 vs XeSS comparison, FSR 4 as advancement, XeSS close to DLSS CNN, FSR 4 less FPS).
23. [23] Hardware Unboxed. DLSS 4 vs FSR 4 vs XeSS. (Benchmark 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). *Kept for consistency with the previous article, but may be removed if not relevant to DLSS.*
25. [25] NVIDIA. DLSS FAQ. (General broker reference). *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). (Benchmark for FSR 4 ghosting/disocclusion improvements, hybrid CNN+Transformer model).
27. [27] NVIDIA. DLSS FAQ. (General liquidity reference). *Kept for consistency with the previous article, but may be removed if not relevant to DLSS.*
28. [28] Avell. The Brazilian gaming market stands out on the global stage. (Reference for growth in the gaming market).