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FastAPI vs Flask: Complete Comparison Guide

Compare FastAPI and Flask on performance, type validation, documentation, and async support. Discover which Python framework is the best fit for your API project.

FastAPI

A modern Python framework for building fast APIs with automatic documentation and type validation. FastAPI leverages Python type hints and Pydantic to automatically validate requests and generates interactive API documentation via Swagger UI and ReDoc. It is async-native and one of the fastest Python frameworks.

Flask

A lightweight Python micro-framework offering maximum flexibility with a minimal core. Flask imposes no choices for databases, validation, or templating and lets developers pick their own tools. It has been widely deployed for web applications and APIs for over fifteen years thanks to its simple, familiar API.

Comparison table

FeatureFastAPIFlask
PerformanceAsync-native — up to 2-3x faster than Flask for I/O tasksSynchronous — suitable for standard web applications
Type validationAutomatic via Pydantic — errors caught before processingManual via Marshmallow, WTForms, or custom validation
API documentationAuto-generated — Swagger UI and ReDoc out of the boxManual via Flask-RESTx, Flasgger, or other extensions
Async supportNative async/await — designed for concurrencyLimited — async possible since Flask 2.0 but not native
Learning curveLow — minimal API, type hints make code self-documentingVery low — one of the simplest Python frameworks
EcosystemGrowing — increasingly more extensions and community packagesMature — hundreds of extensions for every need

Verdict

FastAPI is the clear choice for new API projects in Python. Its automatic documentation, type validation via Pydantic, and async support make it superior to Flask for API development. Flask remains relevant for simple web applications with server-side rendering and for projects where the extensive extension library is indispensable. For teams building an API in 2026, FastAPI has become the standard. Flask is the right tool when simplicity and a proven ecosystem take priority over performance.

Our recommendation

At MG Software, we advise Python teams to choose FastAPI for new API projects. The automatic OpenAPI documentation and Pydantic validation significantly reduce development time and errors. We recommend Flask for simple web applications or when a team already has extensive Flask experience. In our own stack, we fulfill the same need with Fastify and TypeScript, which provides similar benefits to FastAPI — type safety, high performance, and automatic schema generation.

Further reading

Django vs FastAPI comparisonNode.js vs Python comparisonREST vs GraphQL comparison

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Frequently asked questions

For API development, FastAPI is objectively better thanks to automatic documentation, type validation, and superior performance. For simple web applications with templates, Flask can still be the better choice due to its larger extension ecosystem and simpler architecture.
Yes, migration is relatively straightforward since both frameworks use similar routing patterns. The main effort is adding Pydantic models for request validation and converting synchronous routes to async. For large applications, a gradual per-module migration may be the best approach.
Yes, Flask is still relevant, especially for web applications with server-side rendering, internal tools, and prototypes. Its extension ecosystem is vast and its simplicity makes it ideal for smaller projects. For new API projects, however, FastAPI has become the better choice.

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