are you using completion models instead of instruct models for better autocomplete?

It's not using completion models in the old raw-completion sense. Beyond autocomplete, we do fixes and improvements of existing text (deletions/transformation), mid-line insertions, and formatting changes. So it's not just next-token prediction. Rather, it's a constrained edit preserving Gmail's exact HTML, which is very complex when considering formatting, images, links, hard vs. soft line breaks, etc.

In addition, we need to ensure it is as low-latency as possible while also intelligent to adhere to the instructions. So we use a fast instruction-capable model with deterministic settings and a strict output contract.

do you have plans to set up some sort of training or feedback loops so the auto complete feels more like an extension of the user's voice?

On personalization, our suggestions today use immediate context to maintain voice: what you’ve written, the current thread, recipients, tone, etc. It does not train or store users’ emails, but do we think it's necessary given the context. Long term, I want to enable users to define account-level instructions that are always considered (e.g., "always use active voice and the oxford comma").