> For the complete documentation index, see [llms.txt](https://docs.kinesis.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.kinesis.network/getting-started/running-llms-with-kinesis-network.md). # Running LLMs with Kinesis Network Running large language models shouldn’t require navigating fragmented infrastructure, overpaying for idle capacity, or locking into a single cloud. **Kinesis Network** is a unified compute platform designed to simplify and optimize how LLM workloads are deployed, scaled, and managed. It enables developers and teams to access high-performance GPUs on demand, with transparent, True-Util pricing that charges only for what you actually use. Whether you’re fine-tuning models, running inference at scale, or experimenting with new architectures, Kinesis provides a consistent, container-based environment that removes operational friction while maximizing performance, flexibility, and cost efficiency. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.kinesis.network/getting-started/running-llms-with-kinesis-network.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.