Balancing model performance and cost

Caching, prompt versioning, and monitoring are effective strategies for keeping LLM usage costs under control. However, you also recognize that your use cases vary widely: from basic code autocompletion to full bug-fixing across enterprise repositories, and each requires different model capabilities.

Another way to reduce cost is by choosing the right model for the task: faster, less powerful models are often sufficient for simpler tasks, while more complex tasks may require larger, more expensive models with advanced reasoning capabilities.