Run models from Flyte by calling a hosted provider, serving open-weight models on your own GPUs, or deploying the models your tasks train.

Inference

Choose how to run a model based on where it lives and how you call it:

You want to Use
Call a hosted model such as Fireworks, OpenAI, or Anthropic from a task or app Providers
Serve an open-weight LLM on your own GPUs at high throughput vLLM endpoint or SGLang endpoint
Serve a small LLM with minimal setup Ollama endpoint
Serve quantized GGUF weights, a model larger than VRAM, or a model on CPU only llama.cpp endpoint
Serve any model behind your own API FastAPI endpoint or Other frameworks such as Ray Serve, LitServe, and BentoML
Copy Hugging Face weights into your storage before serving them Prefetching models
Serve a model you trained in a task Deploy trained models
Score a dataset on GPUs as a job, with no endpoint Batch inference
Load weights inside a task from object storage Stream model weights

Most hosted providers, and vLLM, SGLang, Ollama, and llama.cpp endpoints, expose the OpenAI API or an API compatible with it. Code written against the OpenAI SDK moves between them by changing the base URL, the API key, and the model name. Some providers, such as Anthropic, need their own SDK. See Providers.