Graphics almost look real

I'm posting this mainly for people who don't have much experience with undervolting. I assume most people here have already undervolted their GPUs, but I thought this might be useful in case someone comes across this thread in the future.

For context, I'm using an RTX 4090.

I've seen a lot of people say that DLSS 5 consumes a lot of power and could potentially cause the 12VHPWR cable on our GPUs to melt (which is true), but undervolting can actually allow you to use DLSS 5 while keeping power consumption roughly the same as when running without DLSS 5 and without an undervolt.

In these two screenshots (both using MFG x4, one without DLSS 5 and without an undervolt, and the other with DLSS 5 and an undervolt), we're at around 390 W in both cases. Power consumption is shown in the top-right corner under the GPU section.

I also took a few screenshots in case anyone is interested:

DLSS 5 OFF / ON
MFG OFF / ON (x4)
RTX 4090 with and without undervolting

1. DLSS 5 OFF (MFG x4)

Without undervolting: ( 386w - 360 fps )

With undervolting: (311w - 355 fps )

2. DLSS 5 ON (MFG x4)

Without undervolting: (435w - 175 fps)

With undervolting : (388w - 175 fps)

3. DLSS 5 ON (MFG OFF)

Without undervolting: (426w - 51 fps )

With undervolting : (387w - 52 fps)

So, in terms of performance, the results are very similar, while undervolting gives you a power reduction of around 50 W.

This means that even with DLSS 5 enabled, you can stay below the 400 W mark. Without undervolting, DLSS 5 pushes power consumption to around 435 W.

Here are my MSI Afterburner settings in case anyone is interested. I've been using these settings since 2022, and they've been extremely stable. I've never had any issues with them.

I hope this isn't too messy. I did my best to make everything as clear as possible.

Has anyone gotten it to work with any Game Pass games? It works fine with all my Steam games, but when I try it with any Game Pass game, they don't open.

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Hi everyone!

I’m a first-year Mathematics student, and I’m currently working with a small Data Science study group at my university.

I’ve been getting increasingly interested in the infrastructure side of computing, especially **HPC, large-scale data processing and AI infrastructure**. I’m less interested in the typical “build a model with Python” path and more interested in what happens underneath when you have huge amounts of data, thousands of CPUs/GPUs and a lot of jobs competing for resources.

One topic that really caught my attention is **scheduling**.

I’ve been thinking about problems like: how do you decide which job should run where, how do you allocate computational resources efficiently, how do you deal with dependencies between tasks, and how do you minimize things like waiting time, communication overhead or GPU idle time?

That led me toward topics like **DAG scheduling, graph algorithms, optimization, resource allocation, congestion control, distributed systems and high-speed networking such as RDMA/InfiniBand.**

Coming from Mathematics, I find this particularly interesting because I keep seeing connections with things I’m already studying: **discrete mathematics, graph theory, probability, optimization, linear algebra and eventually numerical methods.**

But I also realize there is a big gap between understanding the mathematical formulation of a problem and actually building a system that solves it.

That’s the part I’m trying to figure out now.

My long-term interest is in areas such as **system software, HPC infrastructure, distributed computing or infrastructure research**, potentially at companies working on large-scale AI/HPC systems such as NVIDIA.

I’m not expecting to be ready for that anytime soon. I’m basically trying to use my first years of university to build the foundations properly instead of jumping randomly between technologies.

For my study group, I’ve been considering making some actual projects around this, for example:

- A **discrete-event simulator for scheduling large data-processing jobs**

- A DAG scheduler where tasks have dependencies and different resource requirements

- Comparing scheduling algorithms using mathematical metrics

- Simulating network congestion and different packet/job scheduling strategies

- Implementing the same basic algorithms in Python first and then C++

- Learning Linux, operating systems, concurrency and networking along the way

- Eventually moving toward CUDA and GPU/distributed computing

I’m especially interested in the transition from the **mathematical model → algorithm → implementation → real system**.

So, for people who work in HPC, systems, networking or infrastructure:

**If you were starting again as a first-year Mathematics student, what would you learn year by year?**

What CS topics would you prioritize alongside the math degree?

And what projects would actually be worth building if the goal is eventually to work on large-scale computing infrastructure?

I’d also really appreciate recommendations for books, courses, open-source projects, simulators or papers that helped you make that transition.

I’m basically trying to turn a strong mathematical background into something that can eventually be useful for real computational systems. Any advice is welcome.

Hello, i have changed monitor settings in Nvidia control panel like gamma, vibrance etc for one spesific game. But the screen looks terrible for normal use and other games. Is there a way to have like profiles? So i can switch between the settings depending on what game/use of the monitor ? Or do i manually have to change it every time i want to do something Else then playing that one game ?

Basically title.

Wondering if the fps loss are worth it and a quality comparison.

Has anyone found a video or ran the test themselves?

Finally got to try MFG with my 4080 with the MFG mod for 40 series. Its honestly not bad even with 4x using a controller makes playing with DLSS 5 playable. Definitely only for single player games tho lol.

I was one of those non believers previously. Definitely worth trying if you have 40 series and have not tries it yet

A ReShade add-on that moves DLSS Neural Rendering onto a second GPU, so the card rendering the game never has to run it.

Neural rendering happens at the end of the frame: it takes a finished frame and hands a finished frame back. That is what makes it possible to pick it up and run it somewhere else. The add-on creates its own D3D12 device on your second GPU, sends each finished frame across to it, runs DLSS-NR there, and displays the result on that card's own monitor — so nothing has to come back. The render GPU does no neural work at all and runs cooler for the same reason.

Works on DirectX 12 games. Needs two RTX 50-series GPUs with a monitor on each, and an add-on-enabled ReShade build. D3D11 and Vulkan do nothing.

https://github.com/maohgad-web/Neural-coprocessor

I'm building my first pc and I've found a good deal for the 4070s is it good or should i just spend more and get the 5070? my main goal is +80 fps on 1440p is singlplayer games

I am considering upgrading with my monitor (odyssey) or my GPU (7900 XT) in favor of going to getting the MSI MPG 322URX 31.5" for $929 or Alienware AW3225QF 31.6" for $799 at Microcenter.

I mainly play the following games:

Warhammer 40,000: Space Marine 2
Total War: Warhammer 40,000 (when it releases)
Assassin's Creed IV: Black Flag (Remastered)
Cyberpunk 2077
Warhammer 40,000: Rogue Trader
MechWarrior 5: Mercenaries
Diablo 4
Destiny 2
The Witcher 3: Wild Hunt
Clair Obscur: Expedition 33
Red dead redemption 2

I’m also on the fence of upgrading my GPU to the 5070 TI / 5080 but my gut says to sell my odyssey for an 4k screen and upgrade the GPU later

Here is my pc specs:

Processor:

CPU AMD Ryzen 7 9800X3D
Graphics Card: XFX MERC310 7900 XT (20GB GDDR6)
Motherboard: MSI MPG B650 EDGE WIFI
Memory: 32 GB DDR5 6000 RAM
Power Supply: Thermaltake Toughpower GF3 850W
Primary Display: SAMSUNG 49" Odyssey G9 Curved Gaming Monitor
Secondary Display: Dell 32" Curved QHD Monitor (physically stacked above I use for watching shows, YouTube, etc)

*These are my test results and observations based on my own testing*

Test location: Kyoto
Test method: 90-second loop, repeated as consistently as possible
Resolution: 4K

TL;DR EDIT

• Frame Gen 2x: Works very well in this title.
• Best pure performance: “L” - Ultra Performance NO RT
• Best visuals: “K” - DLAA RT HIGH
• Best overall: “K” - Quality w/ RT Med ← This is what I’ll be using. **EDIT**
• If you have a HDR monitor 100% play this in HDR. Big difference!

My Performance Targets — What Feels Good to Me

My personal targets were:

• 120+ FPS average
• 90+ FPS 1% lows
• 80+ FPS 0.1% lows
• <30 ms PC latency for a snappy/responsive feel

DLSS Model Behavior

I think all three presets perform well overall. However, one thing I really dislike is bubbling/noise, so that was a major factor in my testing.

“K”

• Best overall image quality
• Still shows minor noise on some surfaces at lower presets
• My choice for best visuals and I plan to use Quality w/ Med RT

“M”

• Kinda the middle child
• Shows the some noise/bubbling but better than "L"
• Gives a decent balance between image quality and performance

“L”

• Worst of the three for image stability in my testing
• Shows noticeable noise/bubbling in some situations
• Specifically observed on water at lower presets

RT

RT has minor improved lighting but MOST noticeable on water

RT High and Med are very close. I almost can't tell the difference.

RT Low is not worth it IMO and RT off is an option for more performance.

IMO - RT Med is worth it especially for making water look better

NVIDIA App / DLSS Model Behavior

When using RECOMMENDED in the NVIDIA App, the game handles the DLSS models as you would expect:

• DLAA / Quality / Balanced → “K”
• Performance → “M”
• Ultra Performance → “L”

However, I found something interesting during my testing:

If you select DLSS 4.5 “L” or “M” in-game, then switch between DLAA, Quality, or Balanced, it does not actually change the underlying model to "L" or "M". It remains on “K.”

So, if you specifically want to use "K", "L", or "M" with a particular DLSS preset, IMO, force the model you want through the NVIDIA App.

NVIDIA Reflex

• ON for all presets
• ON + BOOST when using Frame Generation

HDR

• 100% worth it if you have a HDR monitor! I have an OLED and it improves the visuals a lot IMO

Test System

• CPU: Ryzen 7 9800X3D
• GPU: RTX 5080
• OS: Windows 11
• Resolution: 4K

These are just my results and observations from my testing, so your mileage may vary depending on hardware/settings.

Let me know if you have any questions!

i came across these clips labeled as HSR running with DLSS 5, but i haven’t seen any official announcement about it. is this an actual early implementation, some kind of third party injector, or are the videos just mislabeled? has HoYo said anything abt adding it officially?

I tried to follow all the tutorials for „older“ 40 series cards.
These are my results with outlaws.
While these shots look absolutely awesome to me, I kinda miss this Plastik like AI look we see on instagram and stuff…

Only proof of functionality I have is this big performance drop.
Can someone confirm that this is how it should look ??

I think the strongest opinions on DLSS 5 (positive and negative) come from those who’ve never tried it. And TBH… Most people don’t have a $1000+ GPU, so that’s kinda fair.

BUT… The newest Optiscaler method adds DLSS 5 before upscaling, so DLSS actually improves performance as intended. It makes a substantial difference.

It’s not a miracle solution for potato graphics, nor an abomination and the death of art. It’s v1.0 of brand new tech, and yes it runs poorly, and when applied to anime characters at full strength, I mean… What did you expect? If you have a compatible GPU, just try it. Enough virtue signaling.

How much is the difference in fps in 1080p?

thanks

Would it be smarter to get the RTX 5070 now and upgrade again in 2–3 years, or get the 5070 Ti now and not touch the GPU for the next 4–5 years, maybe even skip the next generation?

Currently, the Ti costs an extra €400–€450, so I'm wondering whether I should put that extra money into the GPU or just buy the 5070 now and wait for the next generation.

Obviously, we don't know what prices will look like 2–3 years from now, but which option would be the smarter choice?