when I tested fletcher algorithm, its speed was relatively good (although a bit slower than murmurhash)
but its quality was poor, if not very poor.
It ended with a Q.Score at or below 2, and its collision ratio was significantly higher (like 3x higher than average).
It's not too difficult to make a very fast algorithm.
What is difficult is to make one which is both fast and feature good distribution and "random-like" behavior.
If all you need is raw speed, you can test the many variants from SanMayce :
The author concentrated on speed, and as a consequence completed some very fast hashes.
They also badly fail on almost every other smHasher test,
but you could nonetheless make a case that the quality of these hashes is "good enough".
And that's most likely true, depending on usage scenario.
At the end of the day, you"ll need to make some tests to ensure your end-benefit.
A faster hash may nonetheless end up in a global algorithm slow down, due to increased collisions, or longer distinction comparisons.
xxHash has proven to be a performance benefit to several applications not just because of its raw speed,
but also because of its better "randomness" property, and better distribution.
Both aspects matter, and randomness typically matters even more than raw speed.