For device support we've been focusing on 1) any Apple M chip (MacOS) and 2) any decent NVIDIA GPU.
Our model inference via Psionic now works well on those devices (for Qwen 3.5 & Gemma 4) and we expect those same devices to also be able to contribute well to a DiLoCo run, but won't know for sure which devices will be able to realistically contribute to the training run until we start gathering live data from our Pylon network next week as we start pushing our training code live.
We'll cover what we learn each week in our next video episodes, aiming to release every M/W/F.
For device support we've been focusing on 1) any Apple M chip (MacOS) and 2) any decent NVIDIA GPU.
Our model inference via Psionic now works well on those devices (for Qwen 3.5 & Gemma 4) and we expect those same devices to also be able to contribute well to a DiLoCo run, but won't know for sure which devices will be able to realistically contribute to the training run until we start gathering live data from our Pylon network next week as we start pushing our training code live.
We'll cover what we learn each week in our next video episodes, aiming to release every M/W/F.