> For the complete documentation index, see [llms.txt](https://docs.everinfer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.everinfer.ai/getting-started/limitations.md). # Limitations * Only one `engine` instance can be active per API key. Please kindly apply your best effort to completely destroy created engines and associated processes from existence after use. * Hosting multiple models simultaneously requires separate API keys for each model - take a look at [Stable Diffusion](/examples/stable-diffusion-decouple-gpu-ops-from-code.md) demo to see how it is done. * Interrupting Jupyter Notebook kernel does not guarantee `engine` destruction. Please restart the kernel before initializing new `engine`. * Max file size for [each ONNX stage](/getting-started/model-management.md#model-chaining) is 2GB. Uploading models with external weight data will be possible soon. * Max `engine` input and output sizes should be 3GB (although it appears to be coded that way, we did not try anything truly gargantuous so far). * Prediction will time out after 1 minute. Common timeout causes: wrong input types, serialization issues. Please check your inputs. --- # 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.everinfer.ai/getting-started/limitations.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.