the space moved from Consumer to Enterprise pretty fast due to models getting bigger

Sounds like you're very serious about supporting local AI. I have a query for you (and anyone else who feels like donating) about whether you'd be willing to donate some memory/bandwidth resources p2p to hosting an offline model:

We have a local model we would like to distribute but don't have a good CDN.

As a user/supporter question, would you be willing to donate some spare memory/bandwidth in a simple dedicated browser tab you keep open on your desktop that plays silent audio (to not be put in the background and deloaded) and then allocates 100mb -1 gb of RAM and acts as a webrtc peer, serving checksumed models?[1] (Then our server only has to check that you still have it from time to time, by sending you some salt and a part of the file to hash and your tab proves it still has it by doing so). This doesn't require any trust, and the receiving user will also hash it and report if there's a mismatch.

Our server federates the p2p connections, so when someone downloads they do so from a trusted peer (one who has contributed and passed the audits) like you. We considered building a binary for people to run but we consider that people couldn't trust our binaries, or would target our build process somehow, we are paranoid about trust, whereas a web model is inherently untrusted and safer. Why do all this?

The purpose of this would be to host an offline model: we successfully ported a 1 GB model from C++ and Python to WASM and WegGPU (you can see Claude doing so here, we livestreamed some of it[2]), but the model weights at 1 GB are too much for us to host.

Please let us know whether this is something you would contribute a background tab to hosting on your desktop. It wouldn't impact you much and you could set how much memory to dedicate to it, but you would have the good feeling of knowing that you're helping people run a trusted offline model if they want - from their very own browser, no download required. The model we ported is fast enough for anyone to run on their own machines. Let me know if this is something you'd be willing to keep a tab open for.

[1] filesharing over webrtc works like this: https://taonexus.com/p2pfilesharing/ you can try it in 2 browser tabs.

[2] https://www.youtube.com/watch?v=tbAkySCXyp0and and some other videos

If you stream weights in from SSD storage and freely use swap to extend your KV cache it will be really slow (multiple seconds per token!) but run on basically anything. And that's still really good for stuff that can be computed overnight, perhaps even by batching many requests simultaneously. It gets progressively better as you add more compute, of course.

They provide excellent documentation and they’re often very quick to get high quality quants up in major formats. They’re a very trustworthy brand.

https://www.reddit.com/r/LocalLLM/

Everytime I ask the same thing here, people point me there.

I picked up a second-hand 64GB M1 Max MacBook Pro a while back for not too much money for such experimentation. It’s sufficiently fast at running any LLM models that it can fit in memory, but the gap between those models and Claude is considerable. However, this might be a path for you? It can also run all manner of diffusion models, but there the performance suffers (vs. an older discrete GPU) and you’re waiting sometimes many minutes for an edit or an image.

[1]: https://modelscope.cn/

I think, for some definition of “banned”, that’s the case. It doesn’t stop the Chinese labs from having organization accounts on HF and distributing models there. ModelScope is apparently the HF-equivalent for reaching Chinese users.