Balancing cost, energy consumption, and performance in large AI models is essential for ensuring sustainable development. One approach is to adopt optimization techniques such as model pruning and quantization, which reduce the model size without significantly affecting accuracy. Coupling these techniques with the use of modern, energy‑efficient hardware can lower power consumption considerably. Additionally, leveraging cloud platforms that use renewable energy further mitigates environmental impact. Continuous performance monitoring is also crucial; by analyzing energy usage and costs in real time, companies can identify optimization opportunities. This integrated strategy ensures that high‑performance models are achieved without excessive resource consumption, making AI advancements both economically viable and environmentally responsible.