Total noob to this space, correct me if I'm wrong. I'm looking at getting new hardware for inference and I'm open to AMD, NVIDIA or even Apple Silicon.

It feels like consumer hardware comparatively gives you more value generating images than trying to run chatbots. Like, the models you can run at home are just dumb to talk to. But they can generate images of comparable quality to online services if you're willing to wait a bit longer.

Like, GPT OSS 120b, assuming you can spare 80GB of memory, is still not GPT 5. But Flux Shnell is still Flux Shnel, right? So if diffusion is the thing, NVIDIA wins right now.

Other options might even be better for other uses, but chatbots are comparatively hard to justify. Maybe for more specific cases like code completion with zero latency or building a voice assistant, I guess.

Am I too off the mark?

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[–] 5 points 1 year ago (5 children)

Framework has an AI machine on the market.

I haven't used it myself but perhaps it's worth looking into for your project.

https://frame.work/gb/en/desktop?tab=machine-learning

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  • [–] [S] 3 points 1 year ago (4 children)

    I'm aware of it, seems cool. But I don't think AMD fully supports the ML data types that can be used in diffusion and therefore it's slower than NVIDIA.

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  • [–] 2 points 1 year ago (1 child)

    Slower? Yes. But the alternative to a Framework Desktop for home use is a 30-40k Nvidia GPU, so I'm fine with slow.

    Not to mention that it is more than fast enough for common use cases: https://github.com/geerlingguy/ollama-benchmark/issues/21#issuecomment-3164570956

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  • [–] [S] 1 point 1 year ago

    For image generation, you don't need that much memory. That's the trade-off, I believe. Get NVIDIA with 16GB VRAM to run Flux and have something like 96GB of RAM for GPT OSS 120b. Or you give up on fast image generation and just do AMD Max+ 395 like you said or Apple Silicon.

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