<p>Serverless computing has recently become very popular as it simplifies deploying and scaling applications. It enables users to develop and run code as Function-as-a-Service (FaaS) without managing the underlying infrastructure. It offers pay-as-you-go pricing based on usage; however, current pricing models in serverless computing are often static, charging based on execution time and memory usage. The static pricing model can be inefficient, as it needs to account for changes in demand and usage over time, leading to higher costs for developers. This static pricing model needs to reflect the real-time fluctuations in resource demand and availability, resulting in suboptimal pricing that only sometimes aligns with the actual value or Cost of the resources consumed. Furthermore, it does not incentivize efficient resource utilization (i.e., cheaper resources in inactive times) or offer competitive pricing that could benefit providers and users. This paper introduces a Dynamic Serverless Pricing (DSP) model that uses game theory to manage costs and resources better. The DSP model utilizes the Stackelberg game to adjust prices based on demand and usage patterns, encouraging server providers to take advantage of off-peak hours. We evaluated the effectiveness of our approach, and the experimental results showed that our proposed pricing model reduces costs by up to 25% and increases resource utilization compared with an existing pricing model.</p>