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I dare say that’s the joke.

Agree, this post feels like it said very little. “Failed to use glm for a month because sometimes it’s slow and want to try other models too.” Okay, so I guess the only complaint about the model (or the service rather) is that it’s a bit slow.

deser might also just be deserialize shortened, and I was wondering if it was something focused on deserialization only. As such, I didn’t find a quick little note on the etymology to be a particularly egregious waste of words.

The computers in the photo and the layout of the store and signage are also quite strange.

I used to think LG monitors were a good option for high quality 4k high refresh rate monitors. But having owned one of their expensive gamery offerings, it is basically worse in every way compared to an older acer. Worse DP1.4 stability (needs really nice cables to be stable), slow/broken ddc implementation, weird tearing with hdmi output from a Mac.

And I also had an older lg 4k monitor that bricked itself after a power outage, which is apparently a known eeprom issue.

Now this. No more LG for me.

Yes, if it does archiving too that would be perfect.

Not sure, there was a lot of complaints when it rolled out because it was actually peer to peer syncing to other laptops which was causing bandwidth issues for people working on vpn, from planes etc.

I’m not sure if it was actually a well thought out idea, since it’s not like fb has a lack of servers or bandwidth, but I didn’t work on it, so I don’t want to throw too much shade at it.

Hister sounds like something I wanted for a while, but never got around to building. Searching stuff I’ve seen before is most of what I do with a search engine, so having it local and fast would be amazing. Eager to give it a try.

At meta, there was a project for delivering binaries of internally built libraries / binaries to dev laptops using a private ipfs network. This was live for at least some period of time.

Surely you can express this in C++ just as you could in rust…

Yeah, I’m doing TP with two cards. The topology is configured based on yaml files, and if you are not using a predefined config you can just create a new config with your topology.

I’m not even using a 800G cable since they are expensive and I don’t think I need the bandwidth, opting for 400G instead. This just needs a config change for the number of Ethernet links it uses internally. (Apparently these cables are just many 200G links put together.)

I think it’s not really worth it compared to just buying tokens or a coding plan.

My setup has 4090 handling attention while TT accelerators handles MLP. With just a 4090 you can have CPU handle the MLP layers and use a MoE model, assuming sufficiently powerful cpu. I tried that setup with minimax 2.5 before, and was able to eke out around 10 to 15 tps (albeit with a 7965wx cpu)

The software stack is pretty immature, definitely very DIY. Their officially supported models are pretty old at this point, though there’s community support for gemma4, and models with GDN like qwen3.6 is supposedly very close.

The entire stack (minus some binary blobs in firmware) is open source, so if you have the time and persistence you can get whatever you want done.

A few community members have been working on support with llamacpp, where we can have supported operations offloaded to the TT cards, while having unsupported ops running on GPU or CPU. Llamacpp is pretty good at that. The existing kernels could definitely be better, and I’ll try my hand at writing some kernels some time.

Yeah that’s definitely the smarter buy if you want to just have models running quickly. But the cost of 2 p150 and a 4090 was <$5000 for me.

The main issue is the immature software, and somewhat baroque way of writing kernels. Please, buy one and join us.

80tp/s with 5080 3090 combo is wild. I’ve been working with a 4090 and two Tenstorrent p150 cards, and manage only about 30 tps utilizing all three for qwen3.6 27b q8. Guess I got more optimization to do.

Would like to see the perf of their setup with and without mtp and ngram speculative decoding though, as well as parallel decode performance (once llamacpp mtp plays well with multiple slots).

Being in California electricity alone puts this non-competitive with just paying a cloud though.