It's a combination of (1) and something you don't list: I think the frontier labs all have multiple generations of undisclosed models in continuous training. There is no "end point" when it's magically "ready". It's just getting better and better all the time. What they release with a name and a version number is just a marketing / branding exercise.

So what you experience as a "near simultaneous" release is just their decision of when to peel off a release from their current set of in-training models, likely based on how they perceive market and regulatory conditions. They likely see a competitor release and then baseline what they should release based on that and it takes a month or two for them to package it up and push it out the door.

What I can imagine is that for some of the labs, they are being forced to publish models closer and closer to the frontier of what they have in training. Effectively, "falling behind" is your forward pipeline shrinking. Google ran out of forward pipeline. So far Anthropic and OpenAI didn't - but probably, one is shrinking.