FastAPI vs Flask for AI APIs
Short answer: choose based on workload and operational constraints, not benchmark headlines. FastAPI is particularly attractive for typed API contracts, async I/O, automatic OpenAPI documentation, and modern Python AI services; Flask remains a strong choice for simple synchronous services and mature extensions.
FastAPI strengths
- Type-driven request and response validation.
- Automatic OpenAPI and interactive API documentation.
- Natural fit for async I/O-heavy workflows.
- Strong ergonomics for structured AI service contracts.
Flask strengths
- Small conceptual surface.
- Mature ecosystem and broad existing codebase compatibility.
- Good fit for straightforward services where async concurrency is not central.
For AI workloads
LLM calls, vector database requests, object storage, and other network operations can make I/O concurrency important. However, an async framework does not make CPU-bound inference magically faster. Profile the actual bottleneck.
Decision rule
Use FastAPI when typed contracts, async I/O, OpenAPI, and streaming are valuable. Use Flask when simplicity, an existing Flask application, or ecosystem constraints dominate. Either can be production-grade with sound architecture and observability.