The most interesting part of Tinybox isn't just the hardware, but the push for a more vertical integration with tinygrad. We've become so accustomed to the CUDA/PyTorch stack that seeing a serious attempt at a different software-hardware synergy is refreshing, even if the hardware specs or price point relative to DIY homelabs raise some eyebrows for power users. It's more about reducing the friction for researchers who want a "just works" environment without the nightmare of driver/toolkit version hell.

IDK, I feel it’s quite overpriced, even with the current component prices.

I almost sure it’s possible to custom build a machine as powerful as their red v2 within 9k budget. And have a lot of fun along the way.

The incremental price increases between products is funny.

$12,000, $65,000, $10,000,000.

I wonder how much has he sold.

Not sure why they stopped using 6 GPUs in thei builds - with 4 GPUs, both 9070 and rtx6000 come in 2 slot designs, so it easy to build it yourself using a bit more expensive, but still fairly regular motherboard.

With 6 GPUs you have to deal with risers, pcie retimers, dual PSUs and custom case for so value proposition there was much better IMO

I would love to see real-life tokens/sec values advertised for one or various specific open source models.

I'm currently shopping for offline hardware and it is very hard to estimate the performance I will get before dropping $12K, and would love to have a baseline that I can at least always get e.g. 40 tok/s running GPT-OSS-120B using Ollama on Ubuntu out of the box.

"... and likely the best performance/$".

"likely" doesn't inspire much confidence. Surely, they have those numbers, and if it was, they'd publicize the comparisons.

Regarding 2x faster than pytorch being a condition for tinygrad to come out of alpha:

Can they/someone else give more details as to what workloads pytorch is more than 2x slower than the hardware provides? Most of the papers use standard components and I assume pytorch is already pretty performant at implementing them at 50+% of extractable performance from typical GPUs.

If they mean more esoteric stuff that requires writing custom kernels to get good performance out of the chips, then that's a different issue.

Sound like solid prebuilt with well balanced components and a pretty case

Not revolutionary in any way, but nice. Unless I'm missing something here?