I originally started this test because I found the situation around DLSS 5 Neural Rendering on older RTX cards technically strange.

I managed to get the Neural Rendering path executing on an RTX 2070 / Turing under Linux through Proton, without ReShade.

The pipeline is essentially:

Game → NGX/D3D12 proxy → original DLSS → nvngx_dlssnr 310.8 → neural output

The proxy intercepts the relevant NGX/D3D12 calls, keeps the game's original DLSS path, executes the Neural Rendering stage afterward, and returns the resulting frame.

But the more interesting part came from looking at what the GPU is actually executing.

From a single frame, I extracted:

• 176 CUBINs
• 174 kernel launches
• kernels with names such as fused_swin_*_fp8

I then started correlating the launches with their CUBINs and looking at the SASS.

The first result was already interesting: the binaries contain genuinely different implementations depending on the GPU architecture.

For one of the kernels:

• sm_75 / Turing: ~1,040 HMMA.1688.F16 instructions, around 19.7k static instructions
• sm_86 / Ampere: ~520 HMMA.16816.F16, around 14.7k instructions
• sm_89 / newer architectures: around 2.9k instructions and a completely different matrix path

Then I found the important part.

The intended operation appears to be:

FP8 E4M3 × FP8 E4M3 → FP16 accumulator

with a logical matrix tile of:

M16 × N8 × K32

On newer GPUs this can map to a single instruction similar to:

QMMA.16832.F16.E4M3.E4M3

Turing obviously has no native FP8 Tensor Core support.

So on the RTX 2070, the same logical FP8 tile is effectively expanded into:

4 × HMMA.1688.F16

This exact 4:2:1 pattern appeared consistently across the blocks I sampled, including Swin kernels with 32/256/512 channels and ViT kernels.

So this does NOT look like a simple FP32 fallback.

The final matrix math is still running on the Turing Tensor Cores in FP16.

The cost seems to come from:

• software unpacking/conversion of FP8
• ~4× more MMA operations for the same logical tile
• much higher register pressure
• significantly more auxiliary instructions
• stack spilling

And then I found something potentially much more useful.

The modules already contain two versions of several kernels:

*_fp8

and an equivalent kernel without _fp8.

On the RTX 2070, the non-FP8 versions are dramatically smaller and appear to have much lower spill pressure.

For example, one 512-channel QKV kernel goes from approximately:

11,952 instructions / 368 bytes stack per thread

to:

2,624 instructions / 8 bytes stack per thread

That is a huge difference.

This means we may not need to rewrite the matrix kernels from scratch.

The interesting question now is how the runtime selects those variants and what data layout the non-FP8 kernels expect.

Simply redirecting the kernel call is not enough, because the buffers may still contain E4M3-packed weights/activations. The next step is mapping the parameters, memory layout and heap so that the non-FP8 path receives valid data.

If that works, there is a potentially much cheaper Turing path:

avoid the software FP8 expansion entirely and feed the existing FP16/Turing-friendly kernels in their expected format.

And this is why I'm now much more interested in the performance ceiling.

The current performance on Turing may not represent the actual cost of Neural Rendering itself. A large part of the cost may simply be the consequence of forcing an FP8-oriented kernel path onto hardware without native FP8 Tensor Cores.

Given the size difference, spill reduction and the 4× MMA expansion we're seeing, I think a Neural Rendering pass somewhere around the ~15 ms range on an RTX 2070 Mobile may actually be plausible if the correct non-FP8 path can be enabled and the conversion overhead removed.

To be clear: 15 ms is not a measured result yet.

It is an optimization target suggested by what the SASS is showing us.

I'm now modifying the runtime/proxy, mapping the kernel arguments and preparing the buffers in the format expected by the alternative kernels.

The next tests should tell us whether that estimate is realistic.

I’ve made a mod for cyberpunk that enables dlss multiframe gen on 4000 series gpus. The mod works by targeting and intercepting the dll in memory and forcing two values. One changes how many frames the gpu can generate the other backports Blackwell specific frame timing instructions that allows ada to place the frames in the correct positions. This method should be portable to any mfg game.

https://www.nexusmods.com/cyberpunk2077/mods/33286

Hello ! 3 months ago, I found this ASUS 8800 GTS 640MB in a cheap workstation I bought. It was perfectly working but was crazy loud at the same time. 2 days ago, I decided to clean it, repaste it.

- Arctic MX-4 for the GPU.
- 1mm thick thermal pads for the rest.

Perfect. Definitely audible but not as bad as before. A little pic with my T1 build (w/ RTX 3080 Ti FE).

What can I do with it (for fun) ?

I ran a few DLSS 5 tests using the same internal resolution, but at different display resolutions.

DLSS 5 NR OFF

• 3440x1440 - SR Preset L / Performance - 1720x720 internal > 155 FPS / 6.48 ms
• 2560x1080 - SR Preset L / Quality - 1705x714 internal > 160 FPS / 6.25 ms

With NR disabled, the results are almost identical despite the different display resolutions. The internal resolution appears to be the dominant factor, with the higher output resolution costing only 0.23 ms.

DLSS 5 NR ON

• 3440x1440 - SR Preset L / Performance - 1720x720 internal > 104 FPS / 9.72 ms
• 2560x1080 - SR Preset L / Quality - 1705x714 internal > 120 FPS / 8.38 ms

This is where things get interesting.

The internal resolutions are still virtually identical, but increasing the display resolution from 2560x1080 to 3440x1440 now adds 1.34 ms of frame time (almost 6x the display resolution penalty seen with NR disabled.)

So it looks like DLSS 5 Neural Rendering has a significantly stronger dependency on the final/output resolution than the normal rendering path does.

My guess is that the neural rendering workload is heavily accelerated by the Tensor Cores, so its cost doesn't scale purely with the internal render resolution. The output resolution also appears to matter substantially, presumably because the neural model has to process/reconstruct information for the final resolution image.

The scaling isn't linear, though. The internal resolution workload is still being handled by the conventional rendering pipeline, while the neural workload adds another component whose cost scales with output resolution.

In other words, these results make me think DLSS 5 NR changes the usual DLSS performance relationship: internal resolution still matters, but output resolution suddenly becomes a much more important part of the equation.

Obviously, this is based on the current unofficial/leaked DLSS 5 implementation, so the behavior could change significantly in the final release.

Edit: Tested on Mafia the Old Country, max settings.

Liverstream from yesterday night by PlasmaTV for Gaming. Really great insights about DLSS5 (seems like it really is just a "filter" that can be added to anything), AI coding and modding in general.

I find it interesting as AI coding is going to make it so that many feature that Nvidia and other companies want to gate keep to newer hardware will be possibly ported to games not designed for it and unsupported hardware.

Give it a watch, worth it!

This is the worst of the many scenarios where I’ve always noticed ghosting, mainly because of the area being packed with changing neon lights and constantly moving NPCs. I was incredibly surprised to see such a clear visual upgrade while sacrificing only a minimal amount of performance compared to Preset E, yet still remaining essentially on par with Preset D.

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Hey everyone , i currently am running an rtx3070 in 1440p AAA Titles and while it has been solid for the past years it clearly has shown its age in the newer titles , as of right now im considering 3 options and they have quite high prices still so ill get to the point

RTX 4070 SUPER : 850$

4070 Ti super : 950$

5070 : 900$

Which one sounds good for its price ? Also i plan to upgrade the whole rig in 2-3 years from now so i just want something that runs 2k maxed out smoothly

Came across this post from an actual Game Director today, and it feels like the first time an actual lead developer is sitting down with the tech itself rather than just reacting to the initial reveal controversy.

I still think it's miles away from offering a properly balanced experience, but the underlying tech is clearly there. For me personally, the real test will always be how much the AI alters face models and how natural it looks in motion: both during regular gameplay movement and across subtle facial expressions and lip-syncing, aside that, I do not think it's for every artstyle, something akin to KDC2 it does make the game pop-up.

I have GeForce256 SDR in my collection, but I had no idea that my card is actually reference design lol

I found out about this by chance while watching Nvidia’s video for the 25th anniversary of GeForce256

P.S. I received the graphics card with such a scratched GPU already, it’s not my fault that it’s like this

I built a new pc with a WINFORCE 5080 OC + R7 9800X3D and it's amazing.

I was wondering if I could get more from my GPU with an overclocking and/or undervolting. I already installed MSI afterburn and tryed to do an oc but I can't tell if I did it right. I set mem to +2000, core to +200 and power limit at 111% (max it can go).

I also installed 3DMark and tested before and after as you can see in the photo.

Unfortunately the only game I have installed that requires a fairly high demand from GPU is Beamg (At every things max setting it runs at 60/70 fps depending on the map).

Is there anywhere to find them other than the discord server? Like a github or something?

It's so tiring when things are locked behind a discord server.

• AMD Ryzen 7 7800X3D
• ASUS TUF Gaming GeForce RTX 5070 Ti
• ASUS B650 Max Gaming Wifi W
• Corsair 3500X
• NZXT Kraken Plus 240mm
• 32 GB T-Force delta DDR5
• Corsair RS120
• 2 TB Samsung 990 Pro

DLSS5 works best when you train it on real life. There is so much footage and photos of basketball players and basketball stadiums the effect is next level here. This looks like gameplay footage for a game releasing two console generations from now. Sports game players are going to be eating good.

Hi,

lets say i have reflex on with gsync on 120hz display, automatically being locked to 116fps. The game has base 80 fps with framgen off. Now i turn on 2x framegen which should result aprox in 160fps. What will happen now? Does framegen tune down base fps to 58 increasing input lag, so that final fps is 116, or it just generate 80 frames and then discard some of them?

Thanks for answer.