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echelon 2 hours ago

If you're doing professional work in coding or video, you can easily saturate a single H200.

This is what RunPod-type services are for.

For instance, ComfyUI is an abomination that can't do half of what Nano Banana and Seedance 2.0 can do. And you have to sit around and wait 10x longer for single results.

I can rent an H200 for $3.50 an hour. That's INSANELY cheap.

I do not understand this split between hosted APIs and rinky-dink local RTX models. Both suck.

The ideal solution is models we own run on RunPods leveraging H200s.

I can spend $100-200/day on compute making much more value with the model outputs.

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edit: I want to respond to comments, but the damned HN rate limits keep me to five comments a day now because I'm a contrarian and say things that rile up the anti-AI folks.

You don't need to buy an H200. It's a depreciating asset. You rent one. It's cheap to rent.

spockz 2 hours ago | parent | next [-]

Sure, to approach frontier model quality locally we need to have more power. And H200s are a way to get there.

However, we need to use the tools that we have. Even if I wanted to buy a (bunch of) H200 for me and my colleagues and could get the expense approved, they are hard to source where we are.

Yes. You can rent them, but I’m not sure how that affects the IP discussion.

Moreover, not everyone is doing coding and video so we have different tasks that can fit quite well on relatively light laptops (Gemma et al), for relatively directed coding sessions we can make do with RTX cards, or a small step up, all the way to H200 in the workstation. Or pods thereof.

We have the graphics cards and laptops with MLX right now. The H200 will take a year at least to arrive. Better get used to run stuff locally.

zozbot234 2 hours ago | parent | prev [-]

I'll definitely believe that for video generation models, but those are also very compute-intensive for rather middling results.