A study was conducted to provide useful numbers for LLM developers, similar to the "Numbers every Engineer should know" document at Google. The cost of using Large Language Models (LLMs) can be significant, with prices ranging from $0.2c to 6c per 1000 tokens for GPT-3.5-Turbo and GPT-4 respectively. However, it is more cost-effective to use a smaller model, such as GPT-3.5-Turbo, which is roughly 50 times cheaper than GPT-4. Fine-tuning a pre-trained model can also be a cost-effective option, with costs ranging from $7 for fine-tuning a 6B parameter model to $40 for fine-tuning the entire works of Shakespeare. The study highlights the importance of understanding GPU memory and the need for efficient use of resources when working with LLMs.