Not at all. Even the ones that provide a "seed" parameter don't generally 100% guarantee you'll get back the same result.

My understanding is that this is mainly down to how floating point arithmetic works. Any performant LLM will be executing a whole bunch of floating point arithmetic in parallel (usually on a GPU) - and that means that the order in which those operations finish can very slightly affect the result.

They are not, necessarily. Especially when using commercial providers who may change models, finetunes, privacy layers, and all kinds of other non-foundational-model things without notice.