The studies I've seen suggest a factor of ten between best and worst (measured by time taken to accomplish tasks of small or medium difficulty), and my interpretation of the data suggests this might be conservative.
It could be that the lower end degrades disproportionately fast given big, complicated, and/or innovative projects. This is only speculation, but if it does apply it might lead to a much greater differential on Google projects.
It could be that Google is measuring how many programmers are needed to do a given task in a given time. Brooks suggested that three times the number of programmers could do twice the work in a given time. This suggests that, to equal one 10, you'd need something like thirty 1s, and so you might rate a 10 as thirty times as productive as a 1. (And, yes, this implies large projects so you can get large teams up and running. I can complete a simple project in less time than it takes to introduce thirty people to each other.)
Neither of these are likely to give us a factor of 300. Suppose that, for a given type of project, an excellent programmer is forty times as good as a mediocre one, which requires that the mediocre one's effectiveness degrades four times as much. Using the "how many programmers" formula from the last paragraph, it would seem that somewhere close to three hundred floundering 1s could match a challenged 10.
This is a lot of speculation, but it would explain the 300 number. It's also possible it was misreported, or that Google's just exaggerating the difference for some reason.