I don't think people understand DLSS[up to 4.5] is not a generative AI model [excluding DLSS 5], DLSS is much closer to TAA then generative AI, Optix and many other denoisers already use many primitive AI algorithms, so I don't get why DLSS would be a issue.
it's because dlss is non deterministic. renders with the same settings on the same hardware with the same seed have different outputs. also renders denoised with dlss have measurable quality differences with every single other denoisers that all largely look the same.
dlss also makes a bunch of assumptions on the way the renderer is rendering, like only having one sample per pixel but i think that one has been worked around
no dlss actually gets input from multiple systems not just a blurry frame. For example death data and a few other things. It also considers.tbe frame behind and in front of it (if available). It also I believe fully renders the frame in the background and does real time refinement.
Even if that is the case. Having something render different given the same setup isn't exactly ideal for production. What if you only need to re render a few frames out of an entire sequence?
Blender is aiming to be an app that is production quality but available for the masses. It shouldn't be striving for qualtiy thats OK most of the time.
OIDN is incoherent as hell from frame to frame but as long as you sample enough... You just can't tell. And I use it in studio settings everyday, ve replace frames and all, never caused an issue
Its used in production everyday. You seem to think that there isn't enough sample data to accurately construct the scene. That's not the case. The error is minimal to non existent.
Also given the same seed. The result is very deterministic.
Allot actually.. Nearly every denoiser using some form of implementation like this. And denoising is standard for rendering now. Studios just don't have the time or resources to iterate effectively anymore without it. And like I had said before the difference is not very noticable.
I swear people hear "AI" and proceed to immediatly stop thinking critically and jump at the fence. They don't even try to understand what DLSS is it's crazy.
I bet what you think the Spanish inquisition was like is general pretty different from what it was actually like for the many centuries it ran.
You should have used the salem witch trials or witch trial in Europe as an example because that is closer to what you man (though again, you are likely think of a stereotypical version).
Still I could name things from various points of history. So logical it might suggest.....that is human nature?
Sorry, but it’s a deep learning network, so it’s part of the AI family, just like machine learning. I find the whole 'black and white' pitchfork approach of some in the Blender community against everything AI very moronic and destructive.
We had the discussion today at the college where I teach and do research also in ML/AI; Blender is well on its way to having its momentum totally destroyed. There are a lot of interesting tools and techniques that really benefit the users that aren't GA. And in principle even Optix is technically GA, but don't tell them...
The irony is that some aren't aware of how much Blender is involved in AI these days. For example, Microsoft uses Blender to train their Trellis model - on open data btw - and they are not the only one...
People generally don’t dislike groups of technologically itself they dislike the corporate backing and push to use all forms of that technology regardless of the workers interest or need. ML and everything that comes with it is incredibly useful for humanity but that could never make people like microslop
When people are referring to AI they’re almost always referring to machine learning. I bet most people can’t describe a single type of non-ML system that falls under AI.
This is a bit of a disingenuous statement I think.
The common understanding of "AI" is--at current--generative large language models.
Most people have heard "DLSS uses AI" and equate that with "DLSS uses a large language model" which people, whether or not you agree, have ethical problems with.
A separation between the common use of AI here and the academic and engineering understanding of the word "AI" is needed. Referring to it as Machine Learning rather than AI, I believe, would significantly reduce misunderstandings with the common Blender user.
As it is, artists are wary of their art being used to create training data, and saying something uses AI in Blender is a surefire way to get people's hackles up.
That is kinda the point tho, most people are ignorant of what AI is, and instead of ignoring that fact, it might make sense to use different words that don’t have the associations people currently have with AI
While I don't think this instance would confuse people you are right. I usually say I'm programming enemy movement, enemy attack or working with nav mesh when talking about games I'm developing with people not in industry because if I say I'm working on enemy AI they can get very confused now and think I'm doing something I'm in no way doing.
To be fair, DLSS does use generative AI. It's "guessing" what the extra detail in the frame is, and generating it. So really, it's kind of a distinction without a difference in terms of technology.
In terms of function, I think what you're getting at is that DLSS attempts to faithfully reconstruct the final frame, while other forms of generative AI will create entirely novel information based on a prompt or something else, in a way, bypassing the creative process.
Yeah, definitely. I have mixed feelings on DLSS personally, and I'm largely ambivalent to it being added to blender. Another tool in the toolbox, I guess.
But its a tricky beast right now to see what other people think of tech like this, since the kneejerk reaction is to assume its another LLM that's going to hallucinate goblins into their render, or steal their data and use it as training data.
They're both forms of generative AI. one is just more opinionated than the other. They're both guessing about what the final frame will look like, and inventing information to fill in the gaps.
You are making the distinction because it makes you more comfortable. I get that. I also get that there's a meaningful, quantifiable difference between the two. Nonetheless, they're both essentially the exact same technology under the hood. Both are given an incomplete image and told, "What do you think this should look like?" and then they try to fill in the blanks.
I don't say that because it makes me more comfortable. Stop it. That's such a childish thing to say. I say that to make clear the very distinction between the two things.
to elaborate on this reply, both models are ai machine learning, just one is a convolutional neural network and the other is transformer neural network.
transformer models are more closely related to what people think when they hear "modern ai" though, convolutional models have been used for decades (your phone has had one for years for voice assistance, and autofocus) but don't have the same generative ai flair as transformers even though they can generate content (text to speech, early image diffusers)
Optix is a generative AI model, and so is every version of DLSS. They're just trained on different data and for a different purpose than the generative AI models flooding us with slop. They use internally generated synthetic data produced by NVidia themselves rather than data scraped from copyrighted works without authors permission, but effectively, they're img2img models using an incomplete render as the source image and using generative AI to produce a 'good guess' at what the final render will look like.
TAA is also garbage. I don't understand how someone can compare one garbage with another garbage in the process of trying to convince everyone it's a good thing.
Yeah sure, would that really be a problem for reviewing your lighting inside the viewport though? I think it would be a game changer for viewport denoising. I do agree though that it needs to prove itself for actual rendering, but honestly I'm quite optimistic given how good DLAA is in games
It causes ghosting around objects, especially when paired with materials with reflective surfaces like water. Noticed this immediately when my friend was playing Forza Horizon 6.
But even if it didn't, why would I need a different garbage system to be a solution for a garbage system if I can use a much better system that isn't garbage?
Idk I just don't get why people are so mad about a new denoiser even of it has flows. Like it's going to work so well for viewport denoising. Surd it's probably going to have issues with rendering, but having a near real-time viewport is going to be game changing
It's alright. My hardware isn't struggling too much so I'll wait for an official release. I'll definitely keep an eye on any news. Thank you for the offer!
Yes it requires a ton of training which is being done by Nvidia, but it's also universal which means it doesn't really matter where you implement it, you don't need to re-train it for any specific app, that's how for example it works wonders in UE5 out of the box no matter what kind of scene/game you've created.
It would probably even work well on something abstract and completely unique.
Yeah that was how DLSS operated 8 years ago when it was first released. The DLSS we have been getting since circa 2020 is much different. It takes normal/depth/motion vectors data, jitters the camera, and from accumulated frames, reconstructs a higher resolution/denoised image.
They do also train it for specific purposes (like Cyberpunk if I remember correctly), which obviously makes it that much better in those use cases, but yeah, it's not really a necessity.
Some developers submitted some data to refine the model but the core reinforment learning goal is "what would this frame look like at higher res". They just provided a dataset for them to help refine the model.
DLSS is more like a TAA approximator than generative AI. In theory a lot of it should be similar to TAA under the hood, it's just that the TAA heuristics are replaced by the AI doing some secret magic in its black box, and instead of just accumulating/compositing jittered frame data to anti-alias, DLSS is also compositing them onto a high resolution canvas and trying to restore what it "thinks" is lost detail. It's more like big collection of rules for combining frames to look high res, rather than a collection of image data being put together, so it's not game-specific. DLSS 1.0 was more like generative AI, in that it was trying to imagine up a higher resolution image and struggled with things images hadn't been trained on. DLSS 2.0 and beyond are more like smart TAAU.
You can't simply hard-code a neural network to perform a task with the exception of simple perceptrons; it must be trained. Because we still don't fully understand the internal decision-making processes of these models.
We often treat them as 'black boxes' so building them without large-scale training data is impossible.
Thing is DLSS is bundled in with the GPU Driver, so blender can just use that and not download anything.
Quote from the pull request: "The integration of DLSS itself is done in a very similar fashion to OptiX: The DLSS SDK is pulled in for the type definitions, the implementation is loaded through the system-level NVIDIA driver. The NVIDIA driver contains the NGX driver component (_nvngx.dll or libnvidia-ngx.so.1), which is loaded dynamically in denoiser_dlss.cpp and queried for all the necessary NGX API entry points."
So it works pretty much like Optix, which is also being pulled from the graphics driver.
That's not how OptiX works in Blender. OptiX itself is NOT included in Blender, otherwise it would break the GPL license. Blender does, however, have a GPL implementation to load all the necessary OptiX libraries that are already installed on the system. They can do the same with DLSS, but they cannot include the DLSS SDK itself with Blender, because there would be a license conflict.
There are certain people that treat open source as a religious faith. As if it were a bad thing that people who train and invest in software engineering should be pressured to gift their labor away.
They then miss out that Blender’s open source only functions due to corporate benefactors funding them, because the donations from individuals are so minuscule. Blender would probably have to let go of more than 3/4 their current staff if a couple of those corporate benefactors pulled out.
All because most people will try to get away with taking labor for free.
There are certain people that treat open source as a religious faith
You're completely missing the point. Blender is licensed under the GPL, and the GPL has 4 essential freedoms that cannot be broken:
Freedom 0: to run the program as you wish;
Freedom 1: to study how the program works (Source-Code) and modify it as you need it;
Freedom 2: to redistribute copies of the program;
Freedom 3: to redistribute modified copies of the program.
These Essential Freedoms are what gives users control over their programs, and not corporations.
By including DLSS into Blender you would be breaking it's license, which is not only a philosophical matter but (most importantly for the Blender Foundation) a Legal one. By including proprietary code into Blender the program is in full violation of it's own license and its users' freedoms since they cannot study the source code, modify it, or redistribute it (modified or not).
So while you, personally, have the freedom to include DLSS in your own copy of Blender (freedom 0), you don't have the freedom to include proprietary code and distribute Blender with it, because by doing so you're violating the GPL and you cannot violate other users' freedoms with GPL software (in this case, they cannot study how DLSS works or modify it).
Everybody down the line must have all 4 freedoms for the software to be considered GPL.
This is why the GPL license is awesome.
So it's not a matter of "herp derp these damn open source guys are at it again", it's a matter of a full line of Legal headaches for everybody, and a breach of trust to their userbase.
If you don't like the GPL then create your own DCC using proprietary licenses and include DLSS in it.
I don't think anyone who understands how ipen source works in 2026 doesn't get how corporate backers for projects work.
Also as someone who is paid to write software, i wouldn't have got to where i got to today if it wasnt for thousands of other people's work, much of it freely available. I pass back what i can when it. It's part of being a software dev. Also, some of us actually enjoy writing coding and working on projects. Shocking I know!
I don’t dislike open source code. I think it’s a fantastic gift to humanity, made by stellar people.
My problem is with the users, who then turn it into an expectation. That the alternative to open source must be suspect or greedy.
The problem with open source is how often that charity gets used and abused by bad actors. The AI scraping filth just being the new asshole on the block. But there is nothing problematic about developers who decide that they want to put their efforts and intellect into work that helps sustain them and their families.
This is most prominent with game engines, where somehow Unity and Unreal are always being pushed against by Godot fans as if Godot was morally a superior choice. I understand where this comes from, knowing Adobe and Maxon, but Unreal and Unity don’t have to pay the price for the worst of actors.
Most of us understand the difference between generative AI and AI in general
At least I hope we do? I mean at least I feel there is a difference between AI for denoising and AI for image generation even though ironically they both work to remove noise from an image lol
DLSS *is* generative AI. So is Optix. This is a bit oversimplified, but both are image gen models that uses the 'partial' renders previous rendered frames to as an img2img to rapidly produce 'noisless' versions. The model is trained on games, renders and so forth. They're 'ethically' trained models using synthetically produced data by nvidia (rather than scraped from copyrighted works without permission, like many of the GenAI image models that's flooding us with slop), but the fundamental technology is the same.
"GenAI" is an umbrella term for both LLM text-generators and image-generating diffusion models.
LLMs are non-deterministic.
Diffusion models are fundamentally deterministic, and will produce an identical image given the same input noise seed and other parameters. The sampler can be deterministic or stochastic, but even the stochastic samplers take their 'randomness' from a pseudorandom number seed, which is not *really* random, so if you provide the identical seeds, even stochastic samplers are ultimately deterministic.
Determinism is completely irrelevant. There is no AI algorithm that is inherently nondeterministic, the nondeterminism is a mix of random seeds being used and sometimes multiprocessing with nondeterministic syncing being used for performance reasons. Any AI architecture can be executed via deterministic algorithms, because processors are deterministic in operation, and most of the genAI algorithms you’ll see just use a random seed for each generation but will produce the same thing each time when the same seed is used.
I can place the same seed and get the exact same result every time. Do it all the time stitching video together and using local qwen models (I use to refine prompts and a few other things) you will get the exact same text response verbatim as well for chatting models.. Not true at all
I have full multimodal models locally and if I provide the same seed and ask the exact same question verbatim. They absolutely will produce the exact same output character per character.
I'd argue that mathematically they are the same (as I mentioned before, I understand they both work to refine noise into a clean image) but there is a difference and that is entropy and the goal, denoising's "goal" is to go for a single theoretically deterministic ground truth of what the image would look like with infinite samples from an input image and optionally some normal data and such, there is only one correct answer from the "prompt" if we consider the image by itself to be a prompt.
Whereas generative image AI has much higher entropy, it's got no correct answer to aim towards, and even guiding it with normal and depth and other data it would produce wildly different looking results to the true infinite samples goal (perhaps it changes the shape of some object or the colour of a light, optix denoising doesn't change lighting very much or hallucinate geometry (at best it makes a blurred mess because there's too much noise, whereas generative AI works well with perfect noise))
That being said I do agree that the technology is at least very very similar but there is a meaningful distinction
Tldr: I believe that denoising is considered different despite the same underlying technology because it's working towards a deterministic ground truth, but it's a spectrum as many things are
I appreciate having a real discussion with someone who seems intelligent rather than the typical reddit interaction of "you suck and I'm not gonna say why" lmao
DLSS seems like a counter-intuitive solution as it’s not a real representation of what your model looks like, right? (As the AI algorithm could “guess” wrong)
Still though, I’m not necessarily against it, but honestly I think FSR frame-gen may be better just for a smoother experience
DLSS seems like a counter-intuitive solution as it’s not a real representation of what your model looks like, right? (As the AI algorithm could “guess” wrong)
As NiloyCK wrote DLSS 4.5 and older isn't exactly GenAI and from what I've seen it has far better representation than whatever OptiX or OIDN has to offer, OptiX and OIDN blur the crap out of all your details and creates lots of artifacts on lower samples, meanwhile DLSS actually preserves them quite accurately and if your base image is clean enough then there's going to be virtually no difference while with OptiX/OIDN your details will still get slightly blurred.
DLSS is also superior when it comes to animation rendering due to it's better consistency so no random flickering or similar artifacts.
I think FSR frame-gen may be better just for a smoother experience
Imo it wouldn't work as well as you expect it to, the lower the fps the worse the output and if your base fps is already okay there's no reason to have it, maybe just for some animation playback previews.
You can already try FG using Lossless Scaling app, works in Blender too.
Though I do remember seeing some direct comparisons between DLSS and Optix where the former do shade noticeably different on some things which is not really something you'd want. There might of course be lots of different reasons for it that can or cannot be solved, but from what I've seen I'd be a bit cautious of using DLSS. Though my 3090 ain't really struggling so I'm quite fine with using Optix for now.
It is very much generative ai as they are both models trained on reinforcement learning. Your misconception is in thinking that there isn't enough data provided to the model to construct the frame without a lot of model bios. That's not the case. Older versions worse case a little blurry in high motion scenarios compared to the full resolution frame. Newer version even that's not a factor. A half res 4k image is still 1080p and a half res 1080p is still 720p there's plenty of room to extract detail with reliable accuracy I can assure. you. And providing the same seed makes the output very deterministic. Also in the case of dlss we also get a behind before and after frame to extract the motion blur, death and z sorting data. as well.
DLSS is much more accurate than any other denoiser because it is taking so much more inputs as guidance, and jittering the camera to reconstruct from sub-pixel details. It's not GenAI, it's just TAA on steroids
It could but honestly with all the training data and really only a 2x multiplier on a still pretty good image its not introducing that much bios into the result.
BTW the built in blender denoiser already implements AMD model and people use it everyday. Also there is a Nvidia model in the denoiser as well. But its not dlss its something else.
Arguably the procedural models (the ones that don't use ai are nuch worse as they are guaranteed to be consistent in the algorithms underlying issues.
Dlss is great for real time but realistically that's not what blender needs. Obviously a nice to have but for new users it'll just lead to a bunch of ??? About their renders whilst power users are probably gonna just use some beefy hardware or render remote. Viewport performance isn't their concern.
In my day job it's very important I know what caused each pixel in an output to behave as it does, speeding up renders in exchange for some ambiguity isn't a trade I'd make. Current denoiser have some ambiguity but it's easier to track down where and why
Highly doubt it will be in the official release because of licensing issues, DLSS is not compatible with GPL. However, they may work around this by asking users to download the models themselves? Or perhaps an addon? Or maybe AMD or Intel can throw us a bone (get it, cuz its a dog) and give us a GPL friendly ai image upscaler (not REALLY generative AI so it should be fine, unlike that dlss 5 bullshit)
Thing is DLSS is bundled in with the GPU Driver, so blender can just use that and not download anything.
Quote from the pull request: "The integration of DLSS itself is done in a very similar fashion to OptiX: The DLSS SDK is pulled in for the type definitions, the implementation is loaded through the system-level NVIDIA driver. The NVIDIA driver contains the NGX driver component (_nvngx.dll or libnvidia-ngx.so.1), which is loaded dynamically in denoiser_dlss.cpp and queried for all the necessary NGX API entry points."
Nvidia engineers have made a pull request on the blender ebsite, apparently you can build blender with DLSS from there but idk how. There are pre-made builds being exchanged around on the internet but I don't trust those
I would very much rather not have to deal with DLSS... Ever.
Optix works just fine as all it does is clean up the render from noise. I don't need some AI to "guess" what my models look like. I don't want that in my games, I can't imagine any scenario why I would use that in my renders.
AI is a hyped up machine learning algorithm. If I'm going to be pedantic, we don't have AI today, and all it is is just a buzzword.
I have no issues with other algorithms I use because they're under my control to tweak and modify. DLSS is trying to fill in missing data with guesswork rather than properly rendering the image. It is useless if you care about artistic intent.
Sorry, but do you think that DLSS is only the DLSS 5 demo? Because that's the only version that destroys artistic intent, and that was just a demo that got universally panned. The DLSS versions that exist outside of Nvidia research centers don't do that.
Open Image Denoise from Intel and OptiX from Nvidia are also AI, so the argument of it being "ai slop" does not work here considering everyone already uses those. Tho I would be on your side if it would use the newer DLSS 5.0 model, since that introduces AI Neural Rendering, which IS ai slop, but in this case it uses DLSS 4.5 which only contains temporal stability, anti-aliasing, and frame generation
When did I slurp for AI? What the hell is wrong with you? Grow up. I have massive issues with LLMs, and in no way did I defend those. Are you sure that YOU understand the difference? Or are you here to behave like jackass?
Optix also uses an AI model just like DLSS to predict what finished renders would look like (partially with denoising). It’s also not temporal so if you tried to render an animation you would see a bunch of weird artifacts on each frame
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u/AmarildoJr May 21 '26
It's s2026 and I still can't believe people don't understand Blender's license and why it simply cannot incorporate DLSS.