That, or, you know. Ask Claude Code to write all of those unit tests.

Variance in numerical instability across hardware is basically a given, because all the different accelerators implement their "fast paths" in slightly different ways. Modern AI just takes it on the chin.

Anthropic, for example, already has to support both Nvidia CUDA and Google/Broadcom TPUs - AMD aside. And I expect those two to have more architectural and software differences than AMD ROCm and Nvidia CUDA accelerators would.

And yes. If you're wondering how they solved the problem of variance between those two: they didn't! Claude instances that run in the TPU land produce slightly different outputs than those in Nvidia racks! Just not different enough for, you know. Anyone to give a shit. No statistically significant effect on model performance.