With the recent increase in ultra-low power applications, researchers are investigating alternative architectures that can operate on streaming input data. These target use cases require complex algorithms that must be evaluated under a real-time deadline, but also satisfy the strict available power budget. Stochastic computing (SC) is an example of an alternative paradigm where the data is represented as single bitstreams, allowing designers to implement operations such as multiplication using a simple AND gate. Consequently, the resulting design is both low area and low power. Similarly, traditional digital filters can take advantage of streaming inputs to effectively choose coefficients, resulting in a low cost implementation. In this work, we construct six key algorithms to characterize bitstream computing. We present these algorithms as a new benchmark suite: BitBench.