FastAPI vs Flask comes down to what the service is. Pick FastAPI when it's an API that other programs call and your team is comfortable with type hints. Keep Flask when it already works, when it renders HTML, or when it's small. That's our judgment; the versions, Python floors and async facts below are dated 7 October 2026 so you can check it.
FastAPI or Flask for your service?
The picks below are judgment. They assume a team that will keep the service for years. We've left Django out on purpose; Django vs Flask for a database-backed product covers that branch.
| Situation | Pick | Why |
|---|---|---|
| New JSON API with typed contracts | FastAPI | Validation and API docs come from the same type hints |
| Existing Flask API, in production, working | Flask | A working service is worth more than a nicer framework |
| Flask app rendering HTML | Flask | FastAPI's strengths are on the API side |
| ML or LLM model-serving endpoint | FastAPI | Typed request and response models, and generated docs for the consumers |
| Service making many outbound calls | FastAPI | Async I/O fits fan-out, if the team keeps blocking calls out of the event loop |
| Team of Flask veterans with no typing habit | Flask | FastAPI pays off only if people write the types |
| Small webhook receiver | Flask | Little to validate, little to document |
If you're still deciding between REST and something else for the contract itself, choosing an API style before choosing a framework comes first.
What does FastAPI add that Flask does not?
Two things: typed validation and generated OpenAPI documentation. FastAPI's features page lists "Interactive API documentation and exploration web user interfaces. As the framework is based on OpenAPI, there are multiple options, 2 included by default." It also lists "Automatic data model documentation with JSON Schema (as OpenAPI itself is based on JSON Schema)."
The validation comes from Pydantic, which FastAPI's alternatives page describes as "a library to define data validation, serialization and documentation (using JSON Schema) based on Python type hints." The same page says "The class FastAPI itself inherits directly from the class Starlette", so the web layer underneath is Starlette, not something FastAPI wrote from scratch.
The same page is also generous about Flask. FastAPI's author says the "decoupling of parts, and being a 'microframework' that could be extended to cover exactly what is needed was a key feature that I wanted to keep."
On the Flask side, your team adds validation and OpenAPI generation, typically with extensions it picks. That's a real cost and also a real freedom, since you choose the pieces.
In practice, with FastAPI the contract becomes code. The handler's type hints are the schema, and the schema produces the docs, so the API documentation is much less likely to drift from what the service accepts. With Flask you can get there, but someone has to keep the pieces aligned.
Does async make FastAPI faster than Flask?
Not by itself, and neither framework's docs say otherwise. Flask's async documentation is blunt: "Each request still ties up one worker, even for async views." It adds "Async is not inherently faster than sync code." It also says "Flask's async support is less performant than async-first frameworks due to the way it is implemented. If you have a mainly async codebase it would make sense to consider Quart." Async views need pip install flask[async], arrived in Flask 2.0, and extensions that predate async will probably not work with async views.
FastAPI's async page describes the other side. A path operation function declared with normal def "is run in an external threadpool that is then awaited, instead of being called directly (as it would block the server)." So sync handlers are safe in FastAPI. The hazard runs the other way: blocking I/O inside an async def handler stalls the event loop for everyone.
We're not giving you a throughput number. The project's own docs call it "one of the fastest Python frameworks available, on par with NodeJS and Go", which is the project's own claim, and we found no independent benchmark from a primary source. The "5x" and "6-8x faster" headlines on some comparison pages come with no source we could trace, so we've left them out.
In our experience, the decision turns on concurrent outbound I/O. A service that calls five other services per request gains from async. A service whose time goes into one database query per request gains little, because the query is the slow part in either framework.
How stable is each, and which Python does each need?
| Framework | Latest | Date | Python floor | PyPI status | License |
|---|---|---|---|---|---|
| FastAPI | 0.142.2 | 30 September 2026 | >=3.10 | 4 - Beta | MIT |
| Flask | 3.1.3 | February 2026 | >=3.9 | 5 - Production/Stable | BSD-3-Clause |
Those come from the FastAPI PyPI record and the Flask PyPI record. FastAPI shipped 0.1.0 on 8 December 2018 and has reached 0.142.2, so the cadence is frequent: more fixes, and more upgrade notes to read.
The Beta classifier isn't decoration. FastAPI's versioning policy says "Following the Semantic Versioning conventions, any version below 1.0.0 could potentially add breaking changes." Its first instruction is to "pin" the FastAPI version to the latest one you know works for your application. Patch versions are for bug fixes and non-breaking changes, and you shouldn't pin starlette.
The Python floor matters more than it looks. The Python devguide says 3.10 reached end of life on 1 October 2026, which makes FastAPI's floor an already-expired version, and Flask's floor of 3.9 is older still, with 3.9 and earlier no longer supported. Both frameworks will run on supported Pythons, so this is about what you set on your own services: what to do about Python 3.10 reaching end of life covers the upgrade.
What does migrating from Flask to FastAPI involve?
Less than a rewrite, if you don't try to do it in one go. FastAPI's docs describe mounting a WSGI application such as Flask inside a FastAPI app with WSGIMiddleware, which now comes from the a2wsgi package. The older import from fastapi.middleware.wsgi is deprecated. The pattern is app.mount("/v1", WSGIMiddleware(flask_app)), and we're paraphrasing the WSGI page here rather than quoting it. Run both side by side, then move endpoints one at a time and retire the Flask routes as you go.
What usually has to move: request and response models, auth, database-session wiring, and whichever Flask extensions you need to replace. The usual trap is a synchronous SQLAlchemy session called from an async def handler, which blocks the event loop. Keep those handlers as plain def, or move the data layer to async deliberately.
We won't quote a duration. The only migration estimate we found had no source, so the honest number is your own: count your endpoints, migrate one representative one, and extrapolate.
A go/no-go check we'd use. Move if most of these are true:
- Contract drift hurts: consumers hit fields the docs got wrong
- A consumer needs generated clients from an OpenAPI schema
- Handlers fan out to several services and wait on them
- The team already writes typed Python
- No one-off deadline is landing on the same quarter
If you can't tick at least three, stay on Flask.
What do the surveys say about adoption?
Stack Overflow's 2025 survey asked: "Which web frameworks and web technologies have you done extensive development work in over the past year, and which do you want to work in over the next year?" Among all 23,678 respondents, 14.8% said FastAPI, 14.4% Flask and 12.6% Django. Among the 19,460 professional developers it's 15.1% FastAPI, 13.2% Flask and 11.7% Django.
That's near parity. FastAPI leads by 0.4 points among everyone and 1.9 among professionals. The survey doesn't state margins here, so treat the all-respondent gap as within noise and don't read it as FastAPI overtaking anything.
JetBrains and the Python Software Foundation's 2024 Python survey collected responses in October and November 2024 from more than 30,000 Python developers and enthusiasts in almost 200 countries and regions. It reports FastAPI at 38%, Django at 35% and Flask at 34%. We saw no 2025 edition.
Both measure what people report using. Neither measures who's available to hire, in which country, or at what seniority.
What to screen for in each hire
These are our suggestions, kept generic. For a FastAPI hire:
- How they model Pydantic schemas, and whether the models are the contract or an afterthought
- Where blocking calls go: the threadpool or the event loop
- How they pin and upgrade a 0.x dependency
For a Flask hire:
- How they chose validation, auth and migrations when the framework gave them none
- How they test a service with many extensions
- Whether they've shipped async, and what broke
For a Django hire, the Django vs Flask piece has its own screening questions.
What this means for your API stack decision
Stay on Flask unless contract drift, async fan-out or a need for generated clients costs you more than a migration would. In our view, most working Flask APIs should stay put.
If you move, use the mount path: FastAPI in front, Flask mounted behind it, endpoints migrated one at a time. Name an owner for it, and pin FastAPI, since it's pre-1.0 and its own docs tell you to.
On any new service, set the Python floor above 3.10, because it's already out of support.
And hire for typed-API habits, not framework names. Someone who writes clear schemas, keeps blocking calls out of the event loop and pins dependencies will do well in either framework. For the neighbouring stack decisions, Hire developers by tech stack: rates, vetting and interview guides is the next read.
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FAQ
Is FastAPI faster than Flask?
We found no independent benchmark from a primary source, so there's no number here. Flask's docs say "Async is not inherently faster than sync code", and FastAPI runs plain def handlers in a threadpool. The project calls itself one of the fastest Python frameworks, but that's its own claim. Measure your own workload, especially if your time goes into database queries.
Is FastAPI better than Flask?
For an API with typed contracts and generated docs, FastAPI does more out of the box. For a small service, an HTML-rendering app or a working Flask API, Flask is the lower-risk choice. FastAPI is also pre-1.0, with a Beta classifier on PyPI, so you'll pin versions and read upgrade notes.
Can Flask do async?
Yes, since Flask 2.0, with pip install flask[async]. Flask's docs say each request still ties up one worker even for async views, and recommend Quart if your codebase is mainly async. Extensions that predate async support will probably not work with async views.
Can I run Flask inside FastAPI?
Yes. FastAPI's docs describe mounting WSGI applications such as Flask with WSGIMiddleware, which now comes from the a2wsgi package. That lets you run both side by side and move endpoints over one at a time.
Is FastAPI production ready?
In Stack Overflow's 2025 survey, 15.1% of professional developers reported extensive FastAPI work, but its PyPI classifier is "4 - Beta" and the version is 0.142.2. FastAPI's docs say any version below 1.0.0 could potentially add breaking changes and tell you to pin the version. Flask is classified "5 - Production/Stable".
Which is easier to hire for?
The survey data doesn't separate them. In Stack Overflow's 2025 survey, 15.1% of professional developers reported extensive work in FastAPI and 13.2% in Flask over the past year. It measures reported use, not availability, location or seniority, so check candidate numbers in your own market.