And their model is just derived from Qwen3.8-next-flash which you can see when going to their HF page. Not much details to be found about the company apart from the founder who "was named in MIT Technology Review's Innovators Under 35".

Not much innovation here though it seems. More like a marketing stunt to collect VC.

Qwen3.8-next-flash is impressive though, especially with Strata or Basalt as inference engines. On a 5090 laptop with 64GB RAM one can run NVFP4 quants at 120-140t/s decode and 3000-4000t/s prefill.

On Mac it is much slower and the Kapitsa engine probably the best bet. Despite the claim of 29GB RAM for Edge0, in order to be fast you need to have at least a 128GB Mac.

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vardump 18 hours ago | parent [-]

How about Splash on Apple silicon? I've heard it's pretty fast.

https://github.com/incoai/splash

	▲	francisjp 13 hours ago \| parent [-]
		Splash is fast, 2x faster prefill and decode than similar quants on oMLX. At least in my limited, and unscientific, 36 hour+ tests https://github.com/JamesFranc/refactored-parakeet/blob/main/...