upvote
Alternatively you could run it on Strix Halo for $1,000 less, and while it may be slightly slower you won't have to deal with NVIDIA's shit on Linux and worrying about having to use their custom kernels or Ubuntu.
reply
> 48GB of VRAM with, say, two 3090s

So like... $2000+ just for the used GPUs? Plus I assume it's considerably more effort to get it working.

reply
>Plus I assume it's considerably more effort to get it working.

Nah, not really. It is a little annoying in terms of space and power, though. Not every case and motherboard can support cards that big.

reply
The tweet you link shows "Qwen 3.6 35b NVFP4 - 256k ctx, 110 tok/s", but I'm getting only half that, around 50 tok/sec, on a DGX Spark with Qwen3.6-35B-A3B-NVFP4 (via vLLM) plus speculative decode w/EAGLE3. I'd be ecstatic to see 110 tok/sec and I wish they had some more sourcing for the exact config, because it's double what I'm getting.

edit - after actually reading the tweets (had to use xcancel) and visiting the source git repo, switching to MTP for speculative decode makes things a hell of a lot faster, and the abliterated model plus dflash makes it even faster! I'm now seeing 70-90 tok/sec for most stuff. I like!

reply
I think Atlas might also be slightly faster than vLLM:

https://flowtivity.ai/blog/120-tok-s-1m-context-private-ai-d...

reply