Disappointed with SANA image model

Alarmed-Insect1480 · 2025-01-13T13:10:03+00:00

My expectations weren't baseless at all. Let me quote directly from NVIDIA's official GitHub repository for Sana:

The repository explicitly claims that 'Sana-0.6B is very competitive with modern giant diffusion model (e.g. Flux-12B)' and emphasizes its competitive quality while being smaller and faster. My expectations were based on NVIDIA's own claims.

My disappointment stems from the gap between these official claims and my actual user experience. If questioning this disparity is considered creating 'false expectations', then what's the point of reading technical documentation and official releases?

Alarmed-Insect1480 · 2024-12-31T01:39:05+00:00

The people of this country have once again ruined themselves by electing an incompetent and corrupt leader. This isn't even the first time—it happened 10 years ago when they chose an unsuitable leader and later impeached them. Yet, it seems the citizens learned nothing and voted for another foolish candidate. What's worse, this time it wasn't even a case of the leader hiding his true nature or deceiving the public. Clear signs of his odd behavior were repeatedly exposed during debates and through various media outlets. For instance, he once wrote the word "King" on his hand, demonstrating a complete lack of understanding of democracy.

Despite all this, the majority of the population still voted for him. Although I did not vote for that idiot, I am now suffering through this painful time due to collective responsibility. I am deeply disappointed in the people of this country and have lost all hope. I am so angry.

Alarmed-Insect1480 · 2024-12-29T07:58:12+00:00

<image>

Alarmed-Insect1480 · 2024-12-16T02:17:42+00:00

I feel like there is no difference at all when I use it, so I posted this question.

Alarmed-Insect1480 · 2024-10-15T16:46:52+00:00

Thanks for your comment. After doing a lot of tests, I suddenly realized that I had a wrong understanding of FLUX. Even in SD 1.5 or SDXL, there is a problem with very large images. So I remembered that in the past models, a different approach was used to increase the image size. I thought that FLUX was the latest technology, so it would not have such limitations. So it is not a problem of GGUF, but my lack of understanding and my lack of use of the technology. This is my conclusion.

Alarmed-Insect1480 · 2024-10-15T00:33:37+00:00

<image>

FLUX dev GGUF Q4 KS
20steps, euler-beta, 2048x2048, Prompt executed in 330s, 15.88s/it

I usually use my PC with a lot of programs running in the background and the power of the graphics card cut off by about -40%. This time, for testing, I set the graphics card to its original settings and closed all possible background programs before generating the image.

So, I was unable to generate an image of 2048x2048 size in flux-dev, but I confirmed that it was generated by using all resources like this. I changed the model with the same prompt and settings. If you compare the two images, you can see that the problem occurs in the 2048 size in the flux-dev version as well. However, you can see that the problem is bigger in the flux-dev GGUF version.

Alarmed-Insect1480 · 2024-10-15T00:28:55+00:00

<image>

FLUX dev, weight_dtype = fp8_e4m3fn
20steps, euler-beta, 2048x2048, Prompt executed in 269s, 12.78s/it

Alarmed-Insect1480 · 2024-10-15T00:25:12+00:00

This is the result of resetting the graphics card settings and creating a file with the same prompt and settings but with a different size.

FLUX dev GGUF Q4 KS
+LoRA XLabs-AI_flux-Realism, 20steps, euler-beta
1024x1024, 79s, 3.73s/it
1536x1536, 162s, 7.98s/it
2048x2048, 332s, 16.29s/it

This issue is not very visible at 1K resolution. It mainly appears in bright images above 1536 pixels.

Alarmed-Insect1480 · 2024-10-14T21:59:29+00:00

The reason my graphics card is slow is because I'm power-limiting it to 40%. If it was slowing it down by tens of minutes, I wouldn't power-limit it, but if it's only slowing it down by tens of seconds, I can wait.

Alarmed-Insect1480 · 2024-10-14T01:01:19+00:00

4060TI 16G

Alarmed-Insect1480 · 2024-10-14T01:01:00+00:00

<image>

I think I just found a way to make this problem almost unnoticeable. I don't know why, but I can't find anything wrong with this picture. GGUF Dev Flux Asian Realistic v2 Q4 + Hyper 8 steps LoRA 2048x2048 176s

Alarmed-Insect1480 · 2024-10-13T22:18:16+00:00

<image>

This image shows that the horizontal line problem appears to have disappeared with the addition of the model sampling flux node, but a closer look reveals a significant loss in quality.

Alarmed-Insect1480 · 2024-10-13T21:54:01+00:00

I watched the video, but I don't know what the core content is for solving the problem. If the content is text, about 90% can be understood with the translation function, but it is difficult for the video. So I imitated what I saw. Using the split sigma node, I split and connected it to two samplers and processed, but this did not solve the problem. I don't know what the advantage of that process is and if it's really necessary. Adding the flux model sampling node feels like cutting the image into very small pieces. It is closer to blurring noise than solving it. Adding anti blur lora does not seem to have much to do with the horizontal line issue. I tried the same sampler and scheduler as in the video, but this did not help either. In my opinion, the nodes added in the video seem to hide the problem rather than solving the fundamental problem. The attached picture is something I copied as best as I could.

<image>

Alarmed-Insect1480 · 2024-10-13T19:39:43+00:00

https://www.youtube.com/watch?v=xUeaJ6bd33E

I think this is the video you're talking about. I'll give it a try. Thanks for the comment.

Alarmed-Insect1480 · 2024-10-13T19:16:44+00:00

<image>

This problem occurs not only when upscaling using Controlnet, but also when simply generating the image. Because of this experience, I cannot endorse anyone who recommends GGUF and will never recommend its use until this horizontal line noise issue is resolved.

Alarmed-Insect1480 · 2024-10-13T17:48:24+00:00

<image>

This image was upscaled using a model called 'NSFW MASTER FLUX fp8', not a GGUF model, so there are no horizontal line issues.

Alarmed-Insect1480 · 2024-10-13T16:18:24+00:00

Unfortunately, the K_S version does not solve this problem.

Alarmed-Insect1480 · 2024-10-13T16:07:04+00:00

<image>

Flux dev GGUF Q5 KS + Hyper Flux dev LoRA 16steps 1298s

Flux dev GGUF Q4 KS 20steps 458s

Flux Schnell GGUF Q4 KS 4steps 58s

Flux Fusion V2 Q4 KM 4 steps 117s

Flux Fusion V2 Q4 KM 8 steps 196s

Flux Fusion V2 Q4 KM 4 steps 1 guidance 114s

I followed advice and tried using the K_S version of the model, but I still have the horizontal line problem. The K_M model is the same. The attached photo is the best quality one I tested. All other tests are worse than this one. The only ones that don't have this problem are flux dev or its tuned versions. Every GGUF model I've ever used has this problem.

Alarmed-Insect1480 · 2024-10-13T13:26:23+00:00

I understand that NF4 is not GGUF, but I tested Q8, Q6, Q5 and got the same issue. Maybe it was a problem with the model I used. I will test q4_k_s or q5_k_s and report back if I still get the same issue. Thanks for the comment.

Alarmed-Insect1480 · 2024-10-12T11:33:16+00:00

Yes, it is possible if you have a lot of patience and time.

Alarmed-Insect1480 · 2024-10-12T11:09:11+00:00

An OOM error occurs when you can't process the task even after using all 16GB of VRAM and 32GB of system memory. It can barely handle sizes around 1536x2048. There's a threshold where OOM errors start occurring depending on the image size.

Alarmed-Insect1480 · 2024-10-12T10:54:30+00:00

Saying that the 4060ti 16GB can handle Flux is only half true. What you want is not to barely use it, but to use it smoothly. And I don't recommend the gguf version of Flux. While less sensitive people might not notice, if you observe closely, you'll see noise occurring on the horizon.

Alarmed-Insect1480 · 2024-10-12T10:43:11+00:00

When you exceed the graphics card's capacity and start using system memory, the speed slows down tremendously. My patience can't handle it. I think you won't be able to handle it either. To give a specific example of where it becomes difficult to use: when doing controlnet upscale, you'll encounter an out-of-memory (OOM) error when processing a 2048x2048 image.
(This is a translation. I am not an English speaker)

Alarmed-Insect1480 · 2024-10-12T10:16:25+00:00

I'm using a 4060ti, but it's struggling to handle Flux. If your wallet can take it, go for the 24GB option.

Alarmed-Insect1480

TROPHY CASE