Interesting direction. One adjacent pattern we've been working on is a bit less about partitioning a shared node for more tokens, and more about letting developers keep a local workflow while attaching to an existing remote GPU via a share link / CLI / VS Code path. In labs and small teams we've found the pain is often not just allocation, but getting access into the everyday workflow without moving code + environment into a full remote VM flow. Curious whether your users mostly want higher GPU utilization, or whether they also want workflow portability from laptops and homelabs. I'm involved with GPUGo / TensorFusion, so that's the lens I'm looking through.