Energy consumption has been of growing concern in the past few years. Studies have compared the impact of programming languages on energy consumption and performances, and while they generally tend to agree that the most efficient language is CUDA, and that the least efficient one is Python, they have been heavily criticised for their lack of methodology, with some critics saying that the comparison was about the ability of the programmer to code rather than the language itself. With how important energy management has become, we believe that it is important to establish a clear comparison between programming languages so that developpers may be aware of the consequences of their choice when picking a programming language over another. In this work, we developped a new benchmarking framework that allows for the fair comparison of the energy consumption of programming languages. This project did not yield any concrete results per se, but the first partial results suggest that, if execution time is not factored in, power consumption is fairly equivalent between every programming languages.