It's very hard to benchmark things which are that fast, and very easy to make mistakes (for example optimising away the thing you think you are measuring because your benchmark does no real work with it and the compiler notices). So on this homepage you have two benchmarks, which give these stats for stdlib:
Time: ~0.04ms
Memory usage: 2Kb
There is no context here and just a link to another benchmark which most aren't going to bother to read. If your selling point is that you're the fastest, you need to tell people why that's important, and what exactly is faster. These graphs give zero details on the work done, and the timings/memory usage suggest trivial work is done in the benchmark, which means it's likely to be wrong. Is it measuring loading or evaluating or both at once? How many templates, what is in them? Are they properly evaluated with lots of keys in them? Do they test functions, methods, built-in functions?
If you're interested in speed, I'd suggest setting up your own real-world benchmark, with separate charts for parse time (typically done once, of little importance) and evaluation time for sets of templates which are 30-100 templates big and include lots of dynamic content and other templates. That's close to real world use and will tell you if your library is a lot faster, it might even give you far more impressive numbers (reduced render time of typical templates from 100ms to 10ms for example).
Personally, like the parent, fastest is about 10th on my priorities list as long as speed is adequate (and 0.04ms per template is adequate), below: Correctness, Contextual escaping (very handy in stdlib, not supported?), Ease of Use, Partials, Layouts, Syntax, Docs, Adding another dependency, etc.
As a third party dependency for a core feature which would require me to impose your library on everyone who uses my library/app, your argument has to be very strong and there have to be multiple reasons to adopt the library and strong guarantees about future development/support. Speed is not enough, even if it was an order of magnitude better on significantly slower results (say 100ms -> 10ms), it would be just one bullet point and far down the list.
I hope this is helpful.