An important tool to evaluate the performance of any design is an optimal benchmark proposed by O'Quigley and others (2002, Biostatistics 3(1), 51-56) that provides an upper bound on the performance of a design under a given scenario. The original benchmark can be applied to dose finding studies with a binary endpoint only. However, there is a growing interest in dose finding studies involving continuous outcomes, but no benchmark for such studies has been developed. We show that the original benchmark and its extension by Cheung (2014, Biometrics 70(2), 389-397), when looked at from a different perspective, can be generalised to various settings with several discrete and continuous outcomes. We illustrate and compare the benchmark performance in the setting of a Phase I clinical trial with continuous toxicity endpoint and in the setting of a Phase I/II clinical trial with continuous efficacy outcome. We show that the proposed benchmark provides an accurate upper bound for model-based dose finding methods and serves as a powerful tool for evaluating designs.