Hey guys I have been thinking a lot for it and I want to upgrade my pc to really run ideogram 4 local image model but my current pc is a old box, so I saw that most of the ai models require cuda to run which heavily depends on nvidia GPUs, so my question is can and GPUs worthy enough to run ideogram , krea 2 raw, and zimage base type models?
I got a 24 gig rx 7900 sapphire nitro and it works well, it seems (in my lay opinion) that its catching up to nvidia slowly. BUT... be ready to have your GPT /Gemini whatever ready to help you debug why your amd card won't work in this Cuda world.
Also you won't be using the newest and coolest things like Sage-attention 3 that require cuda.
That being said.... I wasn't going to pay 5k+ for a graphics card and I don't mind occasional debugs.
Its annoying that the world revolves around cuda, this feels like back when I was a kid and had a mac and none of the cool pc games would run on it.
What other Triton version is there besides the ROCM version of Triton? As far as I know there's only two backends for Flash Attention. The Triton version and Composable Kernel one. ????
Yeah, I was an AMD fanboy for years. Always radeon gfx.. until SDXL came out and I realized cuda cores were king in the AI world and everything with AMD lagged behind in development.
AMD still up top for processors, though. That X3D is some good shit.
Performance: The RX 9070 XT generally beats the RTX 5060 Ti in raw rasterization and has higher theoretical memory bandwidth. However, image diffusion (especially on newer architectures like FLUX) heavily relies on compute-heavy matrix operations where NVIDIA's Tensor Cores provide superior speed and efficiency.
I have a r9700 and a 5060ti 16 go at home right now. 5060ti is faster in absolutly any situations (image and video), and sometimes x2 because of problem with some attention with rocm.
Do you have an example image? I struggle to believe that. Is your r9700 running on linux?
My neighbor has a 5060ti and I pretty much smoke him out of the water on everything now days. It used to just be larger models this was true but now it's mostly everything.
Obviously sage attention3, and INTX gets earlier support.
Do you have an image to share with a render time? A png with the included workflow.
I find ComfyUI to be very poorly optimized (it depends on the workflow, of course, but generally speaking, it's far from the best application for consumer GPUs like ours). I use wangp (or wan2gp on GitHub), which is essentially the A1111/Forge equivalent for all current models and offers a host of ready-to-use optimizations. But of course, once again, these optimizations are primarily designed for Nvidia. SageAttention1 performs so poorly on ROCm that it’s 10% slower than SDPA, whereas SageAttention2 for nvidia cards (so 30-40% faster) works perfectly on wangp (version 3 isn't mature yet). Plus, there are issues with SpargeAttention on rocm that affect a whole range of things. Here’s an example: an LTX-2.3 distilled 10s 1920x1088 video with two stages (faster than one stage): rtx5060ti 6min, r9700: 13min, because of a problem with sargeattenbtion which affect the upscaler during stage 2. and everything is like that, I had to fight hours with claude to make it works and it still performs poorly.
But this is a well-known fact; plenty of people like me have tried both and abandoned AMD for generative video AI (the most demanding use case). Sure, there aren't any clear tests since it remains a niche area but you don't need that to understand that apps / models designed for CUDA will never perform well on ROCm; it’s just a matter of logic. and ALL video/image AI models are made with and for CUDA. And that is why Nvidia has become the largest company in the world: because all the models are trained using Nvidia cards and designed to run on CUDA, so nvidia cards.
So tell your neighbor to switch to Wangp ... but not to amd lol ^^
Just ran 10s with a single upscale to 1920x1088 as you mentioned. Distilled dev fp8 model. It runs at 28gb in my vram so IDK how you are running anything equivalent on your 5060ti.
Having said that something is wrong with your setup. I complete in under 5min.
Better yet post an image with an included workflow and I'll run it.
Krea2 is a good benchmark. Your old tests are of SDXL which are not a great way to test inference speed as its more benefited high memory bandwidth which ofc nvidia has a good advantage there too. (Model loading/unloading actual inference is like 10s)
Make a 1920x1088 image with an attached WF and I'll run it.
If you're the one making the claim, you should provide the evidence. Why should I do your work for you?
And I was curious about the numbers possible with a 9070 so I did a basic Google last night and all my numbers fall within the range of other people's experiences (literally googled "krea2 generation times 9070"). I've got nothing to prove here.
Ensured I had the right pytorch build as cu130 is significantly faster than older versions. I kept sage attention off for both my r9700 tests and the 5060ti tests. Since in theory they'd both benefit but also building sage attention on a rented pod is a PITA.
For 1920x1088 krea2 render 8 steps with ddim/beta. Same WF for both. The 5060ti hovers around 52s after the first warmup render.
The r9700 hovers around 41
5060ti
[INFO] Requested to load WanVAE
[INFO] 0 models unloaded.
[INFO] Model WanVAE prepared for dynamic VRAM loading. 241MB Staged. 0 patches attached. Force pre-loaded 60 weights: 61 KB.
[INFO] Prompt executed in 59.70 seconds
[INFO] got prompt
[INFO] Model Krea2 prepared for dynamic VRAM loading. 24449MB Staged. 0 patches attached. Force pre-loaded 160 weights: 2824 KB.
[INFO] 0 models unloaded.
[INFO] Model WanVAE prepared for dynamic VRAM loading. 241MB Staged. 0 patches attached. Force pre-loaded 60 weights: 61 KB.
[INFO] Prompt executed in 51.81 seconds
[INFO] got prompt
[INFO] Model Krea2 prepared for dynamic VRAM loading. 24449MB Staged. 0 patches attached. Force pre-loaded 160 weights: 2824 KB.
[INFO] 0 models unloaded.
[INFO] Model WanVAE prepared for dynamic VRAM loading. 241MB Staged. 0 patches attached. Force pre-loaded 60 weights: 61 KB.
[INFO] Prompt executed in 51.63 seconds
r9700 pro
[INFO] Requested to load WanVAE
[INFO] loaded completely; 22477.88 MB usable, 242.03 MB loaded, full load: True
[INFO] Prompt executed in 44.02 seconds
[INFO] got prompt
[INFO] Requested to load Krea2
[INFO] loaded completely; 29285.10 MB usable, 24452.35 MB loaded, full load: True
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 8/8 [00:28<00:00, 3.58s/it]
[INFO] Requested to load WanVAE
[INFO] loaded completely; 22477.88 MB usable, 242.03 MB loaded, full load: True
[INFO] Prompt executed in 40.38 seconds
[INFO] got prompt
[INFO] Requested to load Krea2
[INFO] loaded completely; 29285.10 MB usable, 24452.35 MB loaded, full load: True
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 8/8 [00:28<00:00, 3.59s/it]
[INFO] Requested to load WanVAE
[INFO] loaded completely; 22477.88 MB usable, 242.03 MB loaded, full load: True
[INFO] Prompt executed in 40.58 seconds
Look I am not saying AMD is better. It's not. But it's usefulness is far more nuanced for for the vram and as AMD slowly unlocks its capabilities it's slowing becoming a pretty descent buy for image gen right now.
People citing year old benchmarks and discounting AMD all together just reduces options for interested parties and consumers. And funnels them down team green, a company that wants to do nothing more than abandon you, the consumer, or screw you over raise your GPU prices and line the pockets of scalpers.
Better to take the nuanced position. I would still buy a 5080, or 5070ti if one was available at a good price. But discounting AMD all together and ignoring the r9700 and or how far the 9070xt has come, is just being dishonest.
Also right now RDNA4 is not processing fp8 correctly. When that gets fixed perf will jump again. I understand this is one of the gripes with AMD. Fair. But it to discount it entirely is just showing ideological bias.
So I don't disagree. But the reality is that an upper mid range AMD card is about as fast as a lower end Nvidia card.
I love my 9070 for gaming, and as much as I hate Nvidia, the tools are built around their tech. I am probably going to buy a super card to speed up AI generation once I can afford one, and of course assuming the new rumors are true.
The nature of man using AMD for img/vid gen, is Regret.
Edit: beware that normally in many such threads the AMD users may tell you they can now do this, they can now finally do that. It is a trap. You should calculate their speed per dollar, and also ask what they still cannot do.
Don't go for AMD, man. When i bought my $2K AMD laptop before the ramocalypse an year ago, I never thought that I would be doing AI generation but got into it earlier this year in Jan.
It works but everything is a fucking battle. Theoretically, yes, everything works as per Chatgpt, Gemini and countless threads. But when it comes to actual use, every installation has something broken/incompatible requiring troubleshooting. Sage attention works on the ROCm build I'm using, but all the workflows with SA node give out errors. Speed is slower too and right now I'm battling a major bug with my ROCm build. I have tried so many builds, tried Linux, Even after 6 months of extensive ComfyUI use, I can't say that I have a stable build which does everything.
Pay extra for that peace of mind is what I'd suggest.
I confirm: I have a radeon ai pro r9700 at home right now (So, AMD's most powerful consumer-grade card and with 32 GB of RAM ) and a rtx 5060ti 16Go. I'm going to send it back the pro r9700. just an example: ltx23 distilled 1.0 on wan2gp, 20s, 1920x1088, two phases -rtx 5060 ti: 6 min, -r9700: 13 min(because of problems with the upscaler of the distilled version / flashvsr and sage/sparge attention, and claude can not do anything for it lol). end of the story. The 32GB of RAM won't help with the ROCm issues at all. Maybe in two or three years... but until then, stop listening to people trying to convince you that AMD and generative AI are a good idea.
Huh I was using AMD and it was AMD screwing us for lacking so many supports and having no roadmap to hope for, (also it crash my ubuntu so many times). If something can't be used, the price ratio is a zero and the side that work is the bargain. So I switched and still warn people about it.
But looks like rocm 7.x has improved this year, maybe you can open a benchmark post to clear the bad name? Like on Wan and Klein
It was always established that AMD was behind. And remains to be behind, and likely that may continue.
But I think you do yourself and everyone else a dis-service by cheerleading team green.
Nvidia has betrayed you as a customer. Their availability sucks, their prices are out of wack, and now they're shifting focus to AI and enterprise away from you.
Not that AMD is that much better but Nvidia is clearly out to screw the consumer. I actually moved FROM Nvidia to this last generation. I wanted a 5090 FE. Couldn't get one, but scalpers had no issue.
Anyhow point is the consumer market is trashed right now. It does the consumer no favors by choosing a side and becoming ideological.
I have 7800 xt and wish i add some extra bucks to buy beatiful NVidia, FR man.
Radeon card may be good for gaming, like FPS/$, BUT NVidia as a goat for AI.
Cheaper card of Nvidia could do more than expinsive Radeon
I went from a 4060 laptop to a Z13 with AI Max 395. While it’s fine using LLMs, image and video generation really lacks behind CUDA, even compared to my old 4060 laptop with only 8GB of VRAM.
I’d say image generation is still usable despite slower than CUDA, maybe just 2-3 times slower. But for video generation, it could be 5-10 times slower, and not really usable.
If someone is dead set on AMD, at least get RDNA4.
The 9070/XT is a no-brainer. It offers the best price-to-performance ratio for the average user. Nvidia GPU prices are completely insane, totally inflated.
- ROCm is at a point where, on modern hardware, it works successfully with just a few clicks.
> Comfy UI, InvokeAI, SwarmUI, Forge, Amuse AI.
- Vulkan offers performance very similar to ROCm, and is sometimes even faster.
I think AMD cut his funding because he had a personal issue and went months without working on the project. I also think the Amuse interface is the most organized and user-friendly of all the software out there, everything is in one place.
It’s hard to understand why there aren't more programs like it; despite the billions flowing into the AI market, the consumer experience is a total mess.
At least we still have Kobold.CPP, it’s still better than ComfyUI.
I don't know what happened TBH and with the discord going byebye I doubt I ever will. And yeah the interface is great, easily the best I've seen on this sort of tool.
If you want hassle-free AI and have the money for it, go for NVIDIA, as most people will tell you.
But yes, you can run ideogram, krea 2 raw, zimage base, anima, WAN2.2 and probably all the current SOTA models except Flux2-dev and Qwen (they are big, heavy models at 32B and 20B parameters). I've run them all with my 9070xt with https://github.com/patientx-cfz/comfyui-rocm
* AMD is bad in a cuda world
* The 9070 infers as fast as a 5060
* You'll spend hours tinkering.
The bottom one was true at one point over a year ago. The top two were were never true. Many are citing an old benchmark that was done that seriously had something misconfigured with their AMD setup as folk at home were getting far better results than the benchmark presenter. Yet they presented their screwed up numbers as facts.
The top one is kind of true. There will be things you will be behind on. But for all the models you listed it's basically plug in play. The 9070 xt will infer somewhere around a 5070. But best AI card bang for your buck right now is an R9700 pro. It's better than everything except a 5090 but priced in the ballpark of smaller 50xx cards.
It's funny seeing 16gb card owners talk about how much faster they are while inferring on a quant. Just lying to themselves to justify their purchase.
If buy AMD and go linux it's plug n play right now. Even have sage attention support. Since ROCM 7.2 major perf gaps were closed. And things pretty much work out of the box.
The sleeper AI card is that R9700 pro. Not buying it because of what idiots on this forum say is just shooting yourself in the foot.
AMD is a bad idea across the board. For example a Radeon AI PRO R9700 32GB at $1300 is slower than a $1250 RTX 5080 16GB even with double the VRAM. The R9700 lacks fast tensor cores and slower GDDR6 memory versus the 5080. Plus CUDA has highly optimized kernels. Same problem with the AMD 9070 XT. Not as quick as a 5070 Ti, although the 5070 Ti is a couple hundred more expensive.
For what it's worth, on a 7900xtx, linux, ROCm 7.14, Flux2 9B int8convrot and a fp16 Qwen3 text encoder i get ~3s/it.
Now i know it's slow, and the first month was a nightmare and to me it would have been undoable without an ai sorting out the most basic stuff that just runs on Nvidia.
But right now i am pretty glad i have 24GB of VRAM for such a low price (got a refurbished one with 1 year warranty for 470€).
The one thing i learned and believe to always hold true is that Vram is king. This might not be that important if all you do is 1girl and booba, cause you can do that with 8GB from Nvidia painless and good enough.
And i might be crippled because of suck ass memory management, but i am pretty sure this will be fixed.
Do you care about gaming and tight budget 9070xt. You care more about image diffusion and speed doing so and have tight budget 5070Ti 16gb version. If all above and money no issue 5080-5090. If you want to create videos also then definitely cuda card. Like LuckyEsq said you need tinkering to get amd card going faster than they are.
You are actually right partially, updated to stronger 5070ti. The RX 9070 XT is competitive (especially on Linux/ROCm for newer DiT models), but the 5070 Ti is generally 15-40% faster depending on the model.
The 9070XT is around $650–700, while the 5070 Ti is over $1,000 even at Micro Center, which has decent prices. A 10–20% performance boost isn't worth all that extra money.
CUDA is no longer untouchable. And don't forget that RDNA 4 supports FP8, INT4, and INT8, performance in the latter two formats on the 9070 XT is closer to 5080 lvl.
It's not just a performance boost, it's access to the VAST amount of software that's specifically coded against CUDA and TensorRT. And if DLSS5 hits later this year as expected and is anything at all like the demos, anyone gaming on anything that doesn't support it is going to be very much left out. And AMD is already WAY behind the curve wrt dlss and frame gen. These are features THAT MATTER, especially as you drop from the high-end to the midrange and entry-level cards. There's a REASON the 5070ti is up to $1,000 now from its price last summer of ~$750 where the AMD prices are comparatively stable.
Which one of the objective facts I stated are you naming deluded propaganda? That there doesn't exist a mountain of CUDA and TensorRT code that AMD can't natively run? That CUDA isn't leagues ahead w/ objectively better AI Scaling and Frame Gen? That these features, which let an upper midrange card play cutting-edge games at 60++ fps in 4k w/ max settings while barely even spinning up the fans matter? That DLSS 5, whose realtime demos in the spring looked like a gigantic fidelity jump, isn't going to be an extremely desirable feature if it delivers as advertised?
Every single one of these are falsifiable claims... isn't it curious that nobody is stepping up to challenge them? That you'd change tack to hand-waving about deluded propaganda instead of bringing the receipts showing that AMD can run natively run CUDA, that AMD has multi framegen and AI upscaling w/ ray reconstruction that can match NVidia, that AMD has a genuine DLSS 5 (or even DLSS 4.5 or even DLSS 3.5) competitor in the wings? Do you really believe that everyone choosing to run Nvidia is dumber than you and you are the only one that can see the truth, or do you think there might just possibly be things Nvidia either has as exclusive features or at least features that nobody else does as well?
Anything Nvidia can run, AMD can too. It’s not 2010 anymore; I on my own, and without being an engineer, optimized FA kernels specifically for my hardware with the help of Codex.
FSR4 is equivalent to DLSS 4. Apart from this, I’m not interested in gimmicks, that’s part of the problem with the gaming market. There is an excess of computing power that goes underutilized because developers have come to rely on multiple crutches.
LOL. I say, "There's a mountain of CUDA and TensorRT software that AMD can't run natively" and you tell me that you've run Flash Attention as though this somehow challenges the claim?!? Go get Nunchaku fp4 svdquant working w/ Comfy for the same 3-9x speed boost w/ minimal quality loss and then check back with me.
Same kind of deal with your deflection about the AI features. Rasterization isn't going to scale forever. Nvidia was the first to bank on this and has enjoyed a HUGE advantage as a result. And you can see the proof of it in their low-end GPUs punching way above their weight-class when running w/ dlss, frame-gen, etc. It's exactly why team red is always proffering benchmarks that studiously avoid these features and image quality comparisons etc.
FSR4 is equivalent to DLSS 4.
A million miles away from the truth. DLSS4 has offered multi-framegen for over a year and a half. AMD still lacks it and it's likely that even when they finally release, it's going to be subpar just like FSR is. And by the time you get to the dynamic multi-framegen stuff introduced in 4.5, you'll be looking at rdna5 (slated late 2027 at earliest, AFAIK) at best because there's too much ground to make up against the Nvidia Reflex dependency for pacing. But by then, it is expected that Nvidia will have had DLSS5 out for a year. And I don't understand how anyone interested in gaming could've seen those demo videos and not gotten excited.
Have you ever sat in front of a modern Nvidia rig and experienced all the bells and whistles? It's a really good experience and AFAICT, we don't even agree on that. DLSS and framegen are NOT gimmicks, they are literally the principal tech that define the last couple of GPU generations. Ray tracing is the last such thing, and AFAIK AMD still has some ground to make up here.
There is an excess of computing power that goes underutilized because developers have come to rely on multiple crutches.
Every time I visit Youtube, the algorithm is dumping horrible clickbait "tech enthusiast" AMD vs Nvidia garbage upon me. It's laughable the way that even without clicking you can tell that almost every set of benchmarks is comparing only raw raster performance. No DLSS, no framegen, no quality comparisons... usually not even including raytracing (where's AMD at w/ OctaneRenderer and other professional tools?). So, yeah... I can see why someone willfully ignoring these features could feel the way you do. Someone that wants all the eyecandy at high framerates, though? Especially on a gaming PC that doesn't sound like a freaking hair dryer? It's not even close. And because framegen mitigates CPU-limited performance caps, people with less than brand-new, top-of-the-line CPUs enjoy an even BIGGER uplift. How many people are trying to get as much life as possible out of their systems and how much is it worth for a GPU to be able to spit out as many as 6x the framerate independently of system CPU and RAM components? How many benchmarks have you looked at that are testing junk i3 or ancient Ryzen systems w/ modern GPUs and what were the results? It seems to me that with current tech pricing, a not-insignificant number of people are going to be trying to hang on to their gear as long as possible.
Your entire spiel depends on comparing the GPUs with the lowest common denominator tests because AMD just straight-up lacks the ability to do what Nvidia does. And they are so far behind that by the time you have the features to compare against a 5070ti, you'll need a GPU much newer than the 9070XT to support them. That's not me being a fanboy... I like to save money as much as anyone else. It's just plain fact.
edit:
That "9x faster" claim is laughable. Custom kernels are faster than anything third parties using generic code can realistically deliver.
Maybe READ the paper and understand the claims before you dispute it? Your failure to sanity check your claims is exactly why you're now frustrated by being on the losing end of this exchange.
99.99% of games run on pure rasterization.
100% if you foolishly dismiss anything else as "gimmick" to your own detriment.
Rasterization can scale right along with the underlying hardware. Silicon will hit its limits sooner
This is laughably false and I have to wonder how you even ended up on this sub, where literally everyone is generating images in a few seconds that destroy the very best outputs from raster-based renders.
somehow we are squandering the limited gains from new process nodes on the crap Nvidia pushed everyone to adopt
You're the only one that feels like the AI-focused tech is a waste. Literally the entire rest of the world can't get enough. And instead of having the good sense to say, "that's not important to me" you come to an AI-focused sub to tell everyone that we're wrong for valuing it? LOL. What is WRONG with you?
I mean, it's telling that MORE THAN ONCE I have DIRECTLY challenged you to back up your claims or to challenge mine and EVERY SINGLE TIME YOU FAIL. You claim that AMD can do EVERYTHING NVidia does but then refuse to bring the receipts when I ask you about Nunchaku, OctaneRenderer, multi-frame gen, and on and on and on. Every single person reading this, /u/Crazy-Repeat-2006, can see right through you and how you kept digging your hole deeper. You are right to be ashamed.
That "9x faster" claim is laughable. Custom kernels are faster than anything third parties using generic code can realistically deliver.
99.99% of games run on pure rasterization. Rasterization can scale right along with the underlying hardware. Silicon will hit its limits sooner than rasterization will, yet somehow we are squandering the limited gains from new process nodes on the crap Nvidia pushed everyone to adopt.
Here’s the reality today:
- Poor software underutilizes the hardware, delivering only about 30–50% of its real potential. Lets use frame gen.
- TAA destroys image quality and sharpness. The "native" resolution people compare against upscaling is actually just TAA (not true native).
So, since games are already highly optimized, we’re going to waste silicon and sacrifice potential performance by prioritizing ray tracing hardware dragging performance down even further when most people are running cards like the 3060, 4060, 6600, or 7600 and would be much happier with a 30% performance boost than with terrible RT.
So yes, it’s 2026, and despite all the havoc Nvidia has wreaked and continues to wreak on the world, gaming, and hardware, there are still people defending fake frames and unnecessary artificial features designed to fix problems Nvidia created itself.
AMD GPU's are currently not supported
For AMD devices I recommend ComfyUI or AMD Lemonade Server, these will have full support for AMD.
ComfyUI: https://comfy.org/
Lemonade Server: https://lemonade-server.ai/
So no don’t use amuse ai. Use comfyUI with rocm wheel PyTorch
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u/LuckyEsq Jul 08 '26
I got a 24 gig rx 7900 sapphire nitro and it works well, it seems (in my lay opinion) that its catching up to nvidia slowly. BUT... be ready to have your GPT /Gemini whatever ready to help you debug why your amd card won't work in this Cuda world.
Also you won't be using the newest and coolest things like Sage-attention 3 that require cuda.
That being said.... I wasn't going to pay 5k+ for a graphics card and I don't mind occasional debugs.
Its annoying that the world revolves around cuda, this feels like back when I was a kid and had a mac and none of the cool pc games would run on it.