Fuzzing is a key tool used to reduce bugs in production software.
At Google, fuzzing has uncovered tens of thousands of bugs.
Fuzzing is also a popular subject of academic research.
In $2020$ alone, over $120$ papers were published on the topic of improving, developing, and evaluating fuzzers and fuzzing techniques.
Yet, proper evaluation of fuzzing techniques remains elusive.
The community has struggled to converge on methodology and standard tools for fuzzer evaluation.

To address this problem, we introduce FuzzBench as an open-source turnkey platform and free service for evaluating fuzzers.
It aims to be easy to use, fast, reliable, and provides reproducible experiments.
Since its release in March $2020$, FuzzBench has been widely used both in industry and academia, carrying out more than $150$ experiments for external users.
It has been used by several published and in-the-work papers from academic groups, and has had real impact on the most widely used fuzzing tools in industry.
The presented case studies suggest that FuzzBench is on its way to becoming a standard fuzzer benchmarking platform.