Someone also got the full Q8 R1 running on a $6K PC without a GPU on 2x EPYC with 768GB DDR5 RAM running at 6-8 tok/s [1].

Will be interesting to see the value/performance compared to next gen M4 Ultra's (or Extreme?) vs NVIDIA's new DIGITS [2] when they're released.

[1] https://x.com/carrigmat/status/1884244369907278106

[2] https://www.nvidia.com/en-us/project-digits/

Check out the power draw metrics. Following the CPU+GPU power consumption, it seems like it averaged 22W for about a minute. Unless I'm missing something, the inference for this example consumed at most .0004 kWh.

That's almost nothing. If these models are capable/functional enough for most day-to-day uses, then useful LLM-based GenAI is already at the "too cheap to meter" stage.

I am amazed mlx-lm/mlx.distributed works that well on prosumer hardware.

I don't think they specified what they were using for networking, but it was probably Thunderbolt/USB4 networking which can reach 40Gbps.

Please note that it’s using pretty aggressive quantization (around 4 bits per weight)

This is amazing!! What kind of applications are you considering for this? A part from saving variable costs, fine tuning extensively and security… I’m curious to evaluate this in a financial perspective, as variable costs can be daunting, but not too much “yet”.

I’m hoping NVIDIA comes up with their new consumer computer soon!

Complete aside, but I think this is the first time I’ve seen Apple’s internal DNS outside of Apple.

How is this split between two computers?

Heavily quantized…

Still interesting though.

Fascinating to read the thinking process of a flush vs a straight in poker. It's circular nonsense that is not at all grounded in reason — it's grounded in the factual memory of the rules of Poker, repeated over and over as it continues to doubt itself and double-check. What nonsense!

How many additional nuclear power plants will need to be built because even these incredibly technical achievements are, under the hood, morons? XD