Question: Is there a solution that can help me optimize costs by controlling Large Language Model usage and intelligently managing resources?

If you're looking for a way to control costs by managing Large Language Model usage and optimizing resources, Anyscale is another option. The platform lets you develop, deploy and scale AI applications, including LLMs, with tools like smart instance management, heterogeneous node control and GPU and CPU fractioning for better resource allocation. It can cut costs by up to 50% on spot instances and has native integration with popular IDEs and a free tier with flexible pricing.

Another option is Predibase, which is geared for fine-tuning and serving LLMs with a focus on cost. It has a pay-as-you-go pricing model, free serverless inference for up to 1 million tokens per day, and enterprise-grade security with SOC-2 compliance. Predibase supports a variety of models and offers dedicated deployments with usage-based pricing, so it's a good option for LLM cost management.

If you're looking for a cost-effective and scalable option, Together is another option. It lets you quickly develop and deploy generative AI models with optimized models and scalable inference. Together promises big cost savings, up to 117x compared with AWS and 4x compared with other suppliers, so it could be a good option for companies that want to build AI into their products.

Last, ClearGPT is geared for internal enterprise use, with a focus on security, performance, cost and data governance. It has high model performance, customization and low operating costs, with features like role-based access and data governance. ClearGPT has zero data leakage and offers a secure foundation for AI innovation across enterprise business units, so it's a good option for running LLMs securely and at a low cost.