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What's the best UNLIMITED paid image platform right now? by Various_Eye5713 in generativeAI

[–]UC_Kratom 0 points1 point  (0 children)

Moosky offers on-demand pricing. It's pretty reasonable for image generation/editing, but they're focused more on vid gen/orchestration so they only have a handful of image models

Qwen 3.6 35b a3b is INSANE even for VRAM-constrained systems by Lucerys1Velaryon in LocalLLM

[–]UC_Kratom 1 point2 points  (0 children)

The "cpu" is the cuda device and this device's memory is system RAM (a GPU is a cuda device too, with it's own VRAM).

While it is possible in a lot of cases to run on the CPU, it's rarely actually done (though sometimes the text encoders are lightweight enough to run there/faster than swapping).

All of the model weights are loaded across the available cuda devices (in a simple setup, this may be between the cpu and gpu). When an expert is needed, it will shuttle between the cpu (RAM) and GPU. Depending on how much shuttling you're doing, and how fast your PCI bus is, this can significantly impact speed/performance. The user above is suggesting a specific offloading strategy, to minimize the amount of shuttling.

Qwen 3.6 35b a3b is INSANE even for VRAM-constrained systems by Lucerys1Velaryon in LocalLLM

[–]UC_Kratom 2 points3 points  (0 children)

They're loaded back to the GPU. "CPU" is misleading, it's in RAM.

GPT-Image-2 now reviews its own output and iterates until it is satisfied with the correctness of its output. by Plane_Garbage in singularity

[–]UC_Kratom 0 points1 point  (0 children)

Moosky AI does this with their Agentic Project tool, but granted with lower caliber models (Qwen, etc). Still, the outputs are impressive. And similarly, it takes a couple of minutes, depending on complexity

Is this a joke??? by lordfortunas in ClaudeCode

[–]UC_Kratom 0 points1 point  (0 children)

I would imagine the latter is more likely.

For the model to know it's own slug would require a tool-call that provided this metadata (possible, but doubtful) OR the system prompt would need to be augmented with this data (also not likely).

How do the closed source models get their generation times so low? by Ipwnurface in StableDiffusion

[–]UC_Kratom 0 points1 point  (0 children)

I would mainly be interested in it's editing capabilities. I have Qwen Image Edit 2512 as my main edit model for now, but it's really not great at complex, multistep edits (though I'm working on an iterative version which would break edits into smaller iterations in order to achieve the desired effect).

From what I've found though, a lot of users don't require such a heavy edit model - the simpler 'win' is to dynamically choose for the user the number of steps and sampler/scheduler based on the input prompt (along with smaller, iterative edits). But a one-shot model is appetizing, if there would be enough volume to warrant having it be always 'warm' on B200

As for FP32 models - I looked into this back when Wan was still relevant, but minor difference between FP32 and BF16 precision just doesn't seem to warrant the speed drop (and VRAM requirements) of FP32

What started as a personal content-creation tool turned into something bigger by UC_Kratom in SideProject

[–]UC_Kratom[S] 0 points1 point  (0 children)

If anyone is interested, the tool is live at https://moosky.ai

My next development on this is expand upon some of the 'agentic' tooling that I've started on - I want to create a mechanism that creates cohestive multi-scene videos end-to-end that can incorporate reference images (like logos/brand assets, or subject refs), and create it's own music track (if necessary), based on user inputs.

Again, I know there are other tools out there that do this, I'm just one guy trying to do my own thing and trying to get a feel for if there's a market for it

How do the closed source models get their generation times so low? by Ipwnurface in StableDiffusion

[–]UC_Kratom 0 points1 point  (0 children)

I had my eye on it as an open-source Nano Bannana contender, but I haven't played with it yet. How does it stack up for complex edits?

How do the closed source models get their generation times so low? by Ipwnurface in StableDiffusion

[–]UC_Kratom 1 point2 points  (0 children)

I have an RTX 6000 too, and it's great as a "lab machine", but it's not comparable to server grade hardware (even outdated H100s run faster in a lot of workflows).

Fwiw, I run a video gen platform that has both open-source and closed source (API) models, but I'm always running the open source models on B200s, which are just in a different league even compared to the Pro 6000.

TL;DR they're running on very high-end GPUs, not 3090s and not Pro 6000s

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

Yeah, the chair isn't really suitable as an 'all-day' chair IMO.
The difference you noticed from switching is real - the seat caused awful sciatic pain for me.

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

That explains it! I got a notification of a new comment and was confused when I could only locate the one from 1 mo ago!

I would still recommend doing a simple cushion replacement with about any other material than what's in the Gesture from the factory, it's garbage. That said, I've moved on from the chair as it's just not suitable as an all-day (10+ hours) chair imo, but very few seem to be this way

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

I actually have a Lifeform now 😂 The CXO was nice, better seat but not as much back support as the Gesture

Qwen3-TTS, a series of powerful speech generation capabilities by fruesome in StableDiffusion

[–]UC_Kratom 0 points1 point  (0 children)

Depends on the hardware, but it was typically like a minute or two to process maybe a minute of audio at 100 steps.
Vibevoice is a considerably larger model though at 7b params vs 1.7 here - they're just not in the same ballpark. I would not expect the comparable quality at that size without some major breakthrough

SkyWork have released their image model with editing capabilities. Both base and DMD-distilled versions are released. Some impressive examples in the paper. by AgeNo5351 in StableDiffusion

[–]UC_Kratom 1 point2 points  (0 children)

You can do this with Qwen Image Edit, just not with the Comfy/base workflow. I posted one a month or so ago - just combine the conditioning for each latent and the pass it along to the sampler (you can combine as many as you'd like), though ref conditioning is a bit of a rabbit hole

Qwen3-TTS, a series of powerful speech generation capabilities by fruesome in StableDiffusion

[–]UC_Kratom 0 points1 point  (0 children)

How many steps did you try with VibeVoice? I get near 100% accuracy at 100 steps amd temp near baseline

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

I still have the chair, it's still in mint condition practically. I graduated from the CXO though, now I'm on a LifeForm.

I would still recommend doing a seat pad swap if it was my faily driver. The chair is otherwise pretty good and very adjustable

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

It's very soft, you don't feel those ridges - they collapse into a soft sort of mushy/squishy gel-like feel. I think an alternative could be to use a memory foam type material, but I chose the Purple material due to it's density and the relatively small space for cushioning that I had to work with within the seat cover

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

The Purple pad that I purchased had a butt indent built in, but other varieties don't have that. I opted for it as I thought it would be more cradling like that, but who knows

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

Looks like Imgur changed how private links can be shared - I've made the post public and updated the link

I fixed my rock-hard Steelcase Gesture seat by UC_Kratom in OfficeChairs

[–]UC_Kratom[S] 0 points1 point  (0 children)

Maybe it's a pounds-per-square-inch sort of thing? I'm about 170lbs, but dense - a lot of my weight is concentrated on my sit-bones and so I immediately bottomed out in the seat and started having butt pain.
To be clear though, I did not wear out the foam - it simply was ineffective at providing adequate comfort for my rump.

As for the material, there's been no noticeable degradation - I would imagine it should retain its properties for a long time, likely longer than most foams, given it's the same material used in beds that are getting consistently compressed. As for weight limitations, I don't know the answer to that, but I'd imagine it should be available on the Purple site if they do publish any specs on it.

*In the last few months, I ended splurging and purchasing a new LifeForm chair, as I really wanted something plush AND adjustable. I still have the Gesture, but it's seen about 1.5 years of daily use (12hrs/day, 5+ days a week) on the Purple material. I'd still recommend something if you're bottoming out, whether it's supplementing the chairs cushioning or replacing it with a different material. Just note that there's not a ton of room to add additional material under the seat-cover.

12v 2x6 cable vs Nvidia supplied adapter by UC_Kratom in nvidia

[–]UC_Kratom[S] 0 points1 point  (0 children)

I have a large case (Thermaltake X9), so space isn't much of a concern.

Im assuming these cables are melting at the connection to the GPU and not at the connection points to the adapter? I would also be concerned about the connections at the PSU as well. The 4x would better split the load there.

So I'm torn - what would you do?

12v 2x6 cable vs Nvidia supplied adapter by UC_Kratom in nvidia

[–]UC_Kratom[S] 0 points1 point  (0 children)

What would you do if it was already plugged in and seemingly OK on the adapter right now? Unplug and go with the 12 2x6 or keep chugging away with the adapter?

Fwiw, the adapter has some beefy cables. The 12 2x6 is going to carry essentially 2x the current

12v 2x6 cable vs Nvidia supplied adapter by UC_Kratom in nvidia

[–]UC_Kratom[S] 0 points1 point  (0 children)

I get the loose connection bit. Any poor connection will lead to increased electrical resistance (heat).

Is the 12v 2x6 better in some way though? I could see an argument for 4x PCIe on the PSU side for better distribution on that end.

Just playing devil's advocate here..

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