Right now the speed isn't good for GLM 5.2, Deepseek V4 Flash speed is okay for me (actually reading the output) and quite usable. See kyuz0's great recent video here: https://www.youtube.com/watch?v=PkKXm_mKCCM

With a bit more speed and model improvements, local AI becomes a reasonable practical thing! The biggest problem is all the tech companies making consumer hardware completely unaffordable, and I don't think this is accidental. Look at Micron's profits and share price lately...

I got my Strix machines for ~2k eur each, best computers this 90s kid has ever owned, but those days are gone :(

I'm working on a three node strix halo agentic OS factory designed to be maintained by local agents: https://github.com/projectbluefin/testing-lab

This memory bandwidth combo is amazing for homelabbers. kyuz0's work on these containers has made the investment in this kit so valuable I hope Framework is sending you hardware!

https://projectbluefin.io/server/ is what I'm hoping to ship, designed to just ship setups like this ootb and things like this would be so much harder without kyuz0!

(Note: The 64GB ones are going for $1700-ish empty, the prices on the 128's are outrageous we can just keep making the labs more deterministic over time!)

Would love to see DeepSeek V4 flash/pro and MiniMax M3 benchmarks but already these are pretty impressive, first strix Halo setup I've seen with some serious performance.

EDIT: Apologies - I think I misunderstood these benchmarks - it seems this is actually very slow when compared to a M4 or M5 chip with a good amount of memory. Looking at the creators video here: https://youtu.be/Cfl3TS7ME5s?t=734 -- it seems the performance of strix halo is much much slower than I get on my M4 MBP - which gets ~400 prefill and ~20 tok/s generation

I do hope that apple opens up RDMA for their TB4 machines... ds4 using TB5 macs works great - but there are a lot of capable tb4 (M2/1) machines out there and afaik there's no hardware limitation preventing RDMA from working (at lower bandwidth, but with the latency gains!) on the older stuff.

- 2x Framework Desktop AI Mainboards with 128GB of RAM for $3150 each

- 2x 100G Ethernet controllers for ~$500 each

So the Framework board has a single PCI-e 4.0 x4 slot, which amounts to 8GB/s or 64Gbps theoretical so you're not getting 100G. Also, the 100G cards all seem to be PCI-e x16 slots for obvious reasons so you need a riser or an adapter or something to even get them to work.

I don't know how hot a 100GbE copper NIC runs but, from experience, 10GbE NICs have been basically giant heatsinks, basically. So fiber might be advisable and I expect short fiber cables here probably aren't cost-prohibitive given everything else.

As an aside, if you are using Ethernet for clustering and you're clustering 2 devices, in an ideal world you'd be using simplex Ethernet but that's not an option here.

I wonder if the author considered USB 4.0 for clustering? I ask because I know people who have clustered Mac Studios over TB5 and that bandwidth is up to 120Gbps. The version of USB4 on the Ryzen AI 395 seems to be 40Gbps, which isn't that far off 8GB/s over PCI-e 4.0 x4.

But the limiting factor with Strix Halo (and DGX Spark for that matter) is memory bandwidth, both under 300GB/s. The obvious comparison is to the Mac Studio. Unfortunately the largest spec they currently sell is 96GB. It had been as high as 512GB. And 96GB is $6700+ but you're also getting way better performance AFAICT eg [1]. The M3 Ultra has ~900GB/s memory bandwidth.

You can alternatively buy a Macbook Pro with M5 Max and 128GB of RAM (now $8000, was $5500-6000 a few days ago) but that tops out at ~600GB/s, which is still double these mini AI boxes.

Oh and if you don't want to go the way of these Framework motherboards, you can buy a whole 128GB Strix Halo PC for $3k or less.

I think the main point here though is we're only a few years away from running 300B+ (or even 1T+) param models at useful speeds on enthusiast hardware.

[1]: https://www.reddit.com/r/LocalLLaMA/comments/1u5mfaq/you_can...