software
Flask vs FastAPI 2026: Speed, Features & Best Use Cases
FastAPI is a modern async-first framework built for high-performance APIs with automatic documentation, while Flask is a lightweight, synchronous framework prioritizing simplicity and flexibility. FastAPI handles ~3x more requests per second in benchmarks, but Flask has broader ecosystem maturity and community resources.
F
Flask
Lightweight synchronous Python web framework focused on simplicity and flexibility.
Small-to-medium projects, teams wanting maximum flexibility, learning web development, microservices with moderate traffic, developers prioritizing simplicity over performance.
Score63%
VS
F
FastAPI
Modern Python web framework for building APIs with automatic documentation and async support
High-performance APIs, real-time applications, microservices with high concurrency, modern full-stack projects with FastUI, teams embracing async Python patterns, APIs requiring auto-documentation.
Score63%
Quick Answer
AI SummaryFastAPI is a modern async-first framework built for high-performance APIs with automatic documentation, while Flask is a lightweight, synchronous framework prioritizing simplicity and flexibility. FastAPI handles ~3x more requests per second in benchmarks, but Flask has broader ecosystem maturity and community resources.
Our Verdict
AI-assistedChoose Flask if you're building simple REST APIs, prefer minimal dependencies, need extensive third-party ecosystem support, or value a gentle learning curve for junior developers. Choose FastAPI if you're building modern, high-performance APIs requiring async operations, automatic API documentation, or type-safe request validation out-of-the-box.
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F
Flask
8.7/10
FastAPI
6.3/10
F
F
Choose Flask if
Best pickSmall-to-medium projects, teams wanting maximum flexibility, learning web development, microservices with moderate traffic, developers prioritizing simplicity over performance.
F
Choose FastAPI if
High-performance APIs, real-time applications, microservices with high concurrency, modern full-stack projects with FastUI, teams embracing async Python patterns, APIs requiring auto-documentation.
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Key Differences at a Glance
- Request Handling Speed:✓ FastAPI wins(~22,000 req/s vs ~7,500 req/s)
- Async/Await Support:✓ FastAPI wins(Native built-in vs Manual with extensions)
- Auto-Generated Documentation:✓ FastAPI wins(Automatic (Swagger UI + ReDoc) vs Manual setup required)
Key Facts & Figures
103 numeric metrics compared
| Metric | Flask | FastAPI | Ratio |
|---|---|---|---|
| Core Framework Size(MB) | ~11 KB | — | — |
| Request/Response Latency (simple GET)(ms) | 25-35 ms | — | — |
| Weekly Downloads (PyPI)(thousands) | 850 thousand | — | — |
| Minimal Project Setup Time(minutes) | 5-10 | — | — |
| Stack Overflow Questions (all-time) | 1,200 thousand | — | — |
| Startup Time(milliseconds) | ~150ms | 250-500ms | |
| GitHub Stars(stars) | ~95,000 stars | ~80,000 stars | |
| Related Packages (PyPI)(packages) | ~8,500 | ~2,100 | |
| Time to First API Endpoint(minutes) | 7 minutes | ~5 minutes | |
| Package Ecosystem Size(available packages) | 300,000+ (PyPI) | 500,000+ (PyPI) | |
| Memory Usage (Idle)(MB) | ~35 MB per instance | 50-100MB | |
| Cold Start Time (Serverless)(ms) | ~450 ms | — | — |
| GitHub Stars (Community)(stars) | 68,000+ stars | — | — |
| Available Extensions(count (approx.)) | 2,500+ | — | — |
| Minimum Project Boilerplate(lines of code) | 5-7 lines | — | — |
| Framework Core Size(KB) | ~150 KB | — | — |
| Average Startup Time(seconds) | ~500 ms | — | — |
| Learning Curve for Beginners(hours to proficiency) | 20-30 hours | — | — |
| Market Share Among Web Frameworks(percent) | 70% (Python) | — | — |
| Requests Per Second (Concurrent Load)(RPS) | ~2,500 RPS | — | — |
| Requests Per Second (Benchmark)(req/s) | ~1,200 req/s | — | — |
| Memory Usage (Single Instance)(MB) | 75 MB | — | — |
| Time to 'Hello World'(minutes) | 3 minutes | — | — |
| Available Extensions/Packages(count) | 15,000+ packages | — | — |
| Recommended Learning Duration(weeks) | 2-3 weeks | — | — |
| Job Postings (Global, 2025)(jobs) | 23,500 positions | — | — |
| Production Deployments (Est.)(years in market) | 12+ years | — | — |
| Ecosystem Extensions(packages) | 5,000+ | — | — |
| Time to Build First App(hours) | ~2 hours | — | — |
| Stack Overflow Questions(count (thousands)) | 40,000+ | ~30,000 questions | |
| Concurrent Connection Limit (Practical)(connections) | 500 optimal | — | — |
| Production Deployments(organizations) | ~2.5M active | ~400K active | |
| Third-Party Extensions Available(plugins) | 10,000+ extensions | ~2,500 extensions | |
| Time to Basic Productivity(hours) | 2-4 hours | 4-8 hours | |
| Active Contributors(developers) | 2,500+ | — | — |
| Available Packages/Gems(count) | 500,000+ | — | — |
| Global Job Openings (2024)(positions) | 45,000+ | — | — |
| Minimum Code Boilerplate (Hello World)(lines) | 12 lines | — | — |
| Setup Time to First Running App(minutes) | 8-12 minutes | — | — |
| Average Community Response Time (GitHub Issues)(hours) | 24-36 hours | — | — |
| Throughput (Requests Per Second)(req/s) | ~2,100 req/s | ~32,000 req/s | |
| Package Size(MB) | ~2.5 MB | ~100 KB | |
| Third-Party Extensions(extensions) | 800+ | — | — |
| Production Deployments (Estimated)(count) | 2.5M+ | — | — |
| Throughput (Requests/Second)(req/s) | 400-600 | 8,000-12,000 | |
| Initial Release Year(year) | 2010 | 2018 | |
| Requests Per Second (Throughput)(req/s) | ~7,500 req/s | ~22,000 req/s | |
| Cold Start Time(milliseconds) | ~150ms | 300ms | |
| Memory Usage (Baseline)(MB) | ~30MB | — | — |
| Available Packages/Modules(count) | ~150,000+ PyPI packages | — | — |
| GitHub Stars (Popularity Proxy)(stars) | ~67,000 stars | — | — |
| Time to First Hello World(lines of code) | 4 lines | — | — |
| Default Dependencies(count) | 1 (werkzeug) | 6 (starlette, pydantic, etc.) | |
| Time to 'Hello World' App(lines of code) | 4-5 lines | 8-10 lines | |
| Memory Usage (base)(MB) | ~10MB | ~10MB | |
| Third-party Packages(packages) | 2,000+ packages | 2,000+ packages | |
| Latency (p99 response time)(ms) | 8-12 ms | 8-12 ms | |
| Production Adoption Rate(percent) | 22% (Stack Overflow 2024) | 22% (Stack Overflow 2024) | |
| First Release Year | 2018 | 2018 | |
| Framework Requests Per Second(req/s) | 10,000 | 10,000 | |
| Idle Memory Usage(MB) | 50-80 | 50-80 | |
| Python/Go Package Ecosystem Size(packages) | 400,000+ | 400,000+ | |
| Time to Production (Small API)(hours) | 4-8 | 4-8 | |
| Average Latency (Hello World)(ms) | ~85 ms | ~85 ms | |
| PyPI Weekly Downloads(downloads) | ~2.8M (Jan 2026) | ~2.8M (Jan 2026) | |
| Time to Hello World API(minutes) | ~5 minutes | ~5 minutes | |
| Throughput Performance(requests/second) | ~15,000 req/s | ~15,000 req/s | |
| Memory Usage (Hello World)(megabytes) | ~40 MB | ~40 MB | |
| Throughput Benchmark (requests/sec)(req/s) | ~18,000 req/s | ~18,000 req/s | |
| Framework Age(years) | 6 years (2018) | 6 years (2018) | |
| Time to Build Basic CRUD App(minutes) | 3.5 hours (manual setup required) | 3.5 hours (manual setup required) | |
| Ecosystem Size (package repositories)(packages) | ~480,000 packages (PyPI) | ~480,000 packages (PyPI) | |
| Weekly npm Downloads(downloads) | ~1.2M (PyPI: ~2.8M) | ~1.2M (PyPI: ~2.8M) | |
| Core Library Size(kilobytes) | 1,200KB (with uvicorn) | 1,200KB (with uvicorn) | |
| Performance - Request Throughput(requests/sec) | ~15,000-18,000 req/sec | ~15,000-18,000 req/sec | |
| Request Throughput(requests/second) | ~12,000 req/s | ~12,000 req/s | |
| Cold Start Latency(milliseconds) | 300ms | 300ms | |
| Weekly Package Downloads(millions) | ~450,000 (PyPI) | ~450,000 (PyPI) | |
| Production Maturity(years) | 7 years | 7 years | |
| P99 Latency (typical)(ms) | 150-250 | 150-250 | |
| Peak Throughput (Req/s)(requests per second) | ~10,000 req/s | ~10,000 req/s | |
| Memory Usage per Process(MB) | ~40 MB | ~40 MB | |
| Community Library Ecosystem(total packages) | 500,000+ PyPI packages (Python ecosystem) | 500,000+ PyPI packages (Python ecosystem) | |
| Job Market Postings (2026)(active positions) | ~12,000 positions | ~12,000 positions | |
| Framework Maturity(years) | 6 years (released 2018) | 6 years (released 2018) | |
| Minimum Memory Footprint(GB) | 40MB | 40MB | |
| GitHub Stars (as of 2026)(stars) | 68,000+ stars | 68,000+ stars | |
| NPM Weekly Downloads(downloads) | 2.5M weekly | 2.5M weekly | |
| Time to Production Hello World(minutes) | 5 minutes | 5 minutes | |
| Built-in Features Count(features) | 12 core features | 12 core features | |
| Production Applications (market estimate)(thousands) | 45,000+ apps | 45,000+ apps | |
| Active Job Listings (2025)(positions) | 42,000 | 42,000 | |
| Memory Usage (Idle Instance)(MB) | ~80-120 MB | ~80-120 MB | |
| Requests Per Second (Single Instance)(req/s) | ~7,500 req/s | ~7,500 req/s | |
| Memory Footprint Per Process(MB) | ~15 MB | ~15 MB | |
| Time to Basic API (Hello World)(lines of code) | ~5 lines | ~5 lines | |
| Ecosystem Size (Packages)(packages) | ~350,000 PyPI packages (FastAPI-specific: ~4,000) | ~350,000 PyPI packages (FastAPI-specific: ~4,000) | |
| Application Startup Time(seconds) | 150ms (average) | 150ms (average) | |
| Requests Per Second (1KB payload)(req/s) | ~28,000 | ~28,000 | |
| Available Packages/Libraries(count) | ~500,000 (PyPI) | ~500,000 (PyPI) | |
| NPM/PyPI Weekly Downloads(weekly downloads) | ~2.8M (PyPI/month) | ~2.8M (PyPI/month) | |
| Lines of Code for Basic Endpoint(lines) | 5-8 lines | 5-8 lines | |
| GitHub Stars (2026)(stars) | 75,000+ | 75,000+ |
Sourced from publicly available data ·
Key Differences
7 attributes compared head-to-head
F
3FlaskFastAPI leads
F
4FastAPIFlask
Attribute
FastAPI
- ~7,500 req/sRequest Handling Speed~22,000 req/s(winner)
- Manual with extensionsAsync/Await SupportNative built-in(winner)
- Manual setup requiredAuto-Generated DocumentationAutomatic (Swagger UI + ReDoc)(winner)
- Manual or extension-basedData ValidationBuilt-in with Pydantic(winner)
- Minimal (50-100 lines for basic app)(winner)Learning CurveModerate (100-150 lines)
- ~95,000 GitHub stars(winner)Community Size~80,000 GitHub stars
- 15+ years (since 2010)(winner)Production Maturity5+ years (since 2018)
- Request Handling Speed
Flask
~7,500 req/s
FastAPI
~22,000 req/s(winner)
- Async/Await Support
Flask
Manual with extensions
FastAPI
Native built-in(winner)
- Auto-Generated Documentation
Flask
Manual setup required
FastAPI
Automatic (Swagger UI + ReDoc)(winner)
- Data Validation
Flask
Manual or extension-based
FastAPI
Built-in with Pydantic(winner)
- Learning Curve
Flask
Minimal (50-100 lines for basic app)(winner)
FastAPI
Moderate (100-150 lines)
- Community Size
Flask
~95,000 GitHub stars(winner)
FastAPI
~80,000 GitHub stars
- Production Maturity
Flask
15+ years (since 2010)(winner)
FastAPI
5+ years (since 2018)
Full Comparison
| Attribute | Flask | FastAPI |
|---|---|---|
| Core Framework Size(MB) | ~11 KB | — |
| Request/Response Latency (simple GET)(ms) | 25-35 ms | — |
| Startup Time(milliseconds) | ~150ms(winner) | 250-500ms |
| Framework Core Size(KB) | ~150 KB | — |
| Average Startup Time(seconds) | ~500 ms | — |
Show 23 more attributesRequests Per Second (Concurrent Load)(RPS) ~2,500 RPS — Requests Per Second (Benchmark)(req/s) ~1,200 req/s — Throughput (Requests Per Second)(req/s) ~2,100 req/s ~32,000 req/s Throughput (Requests/Second)(req/s) 400-600 8,000-12,000 Requests Per Second (Throughput)(req/s) ~7,500 req/s ~22,000 req/s Cold Start Time(milliseconds) ~150ms 300ms Memory Usage (Baseline)(MB) ~30MB — Memory Usage (base)(MB) ~10MB — Latency (p99 response time)(ms) 8-12 ms — Framework Requests Per Second(req/s) 10,000 — Average Latency (Hello World)(ms) ~85 ms — Throughput Performance(requests/second) ~15,000 req/s — Throughput Benchmark (requests/sec)(req/s) ~18,000 req/s — Performance - Request Throughput(requests/sec) ~15,000-18,000 req/sec — Request Throughput(requests/second) ~12,000 req/s — Cold Start Latency(milliseconds) 300ms — P99 Latency (typical)(ms) 150-250 — Peak Throughput (Req/s)(requests per second) ~10,000 req/s — Memory Usage (Idle Instance)(MB) ~80-120 MB — Requests Per Second (Single Instance)(req/s) ~7,500 req/s — Memory Footprint Per Process(MB) ~15 MB — Application Startup Time(seconds) 150ms (average) — Requests Per Second (1KB payload)(req/s) ~28,000 — | ||
| Built-in Database ORM(feature) | None (use SQLAlchemy separately) | — |
| Admin Interface | Requires manual or third-party setup | — |
| Native Async/Await Support | Experimental in Flask 2.0+ | Native first-class support |
| Built-in Data Validation | No (manual or extension-based) | Yes (Pydantic integration) |
| WebSocket Support | No (requires Flask-SocketIO) | — |
Show 12 more attributesData Science Library Integration Native (NumPy, TensorFlow, Pandas) — Built-in ORM Support Via SQLAlchemy extension — Built-in Admin Dashboard No, requires build — Async Request Support Full native support — Auto API Documentation Native (Swagger UI + ReDoc built-in) — Built-in ORM No (requires external library) — Auto-generated API Documentation Yes (automatic) — Built-in API Documentation Yes (Swagger UI + ReDoc automatic) — Native Type Validation Yes (Pydantic built-in) — Built-in Authentication No (requires FastAPI-Users, python-jose) — Database ORM Included No (requires SQLAlchemy, Tortoise-ORM) — Auto-Generated API Docs Yes (Swagger/ReDoc) — | ||
| Weekly Downloads (PyPI)(thousands) | 850 thousand | — |
| Weekly npm Downloads(downloads) | ~1.2M (PyPI: ~2.8M) | — |
| Weekly Package Downloads(millions) | ~450,000 (PyPI) | — |
| NPM Weekly Downloads(downloads) | 2.5M weekly | — |
| Minimal Project Setup Time(minutes) | 5-10 | — |
| Minimum Code Boilerplate (Hello World)(lines) | 12 lines | — |
| Setup Time to First Running App(minutes) | 8-12 minutes | — |
| Time to Build Basic CRUD App(minutes) | 3.5 hours (manual setup required) | — |
| Lines of Code for Basic Endpoint(lines) | 5-8 lines | — |
| Stack Overflow Questions (all-time) | 1,200 thousand | — |
| Authentication Built-in | No (use Flask-Login or similar) | — |
| Auto-Documentation Support | Manual integration required | Built-in (OpenAPI 3.0) |
| Time to 'Hello World'(minutes) | 3 minutes | — |
| Recommended Learning Duration(weeks) | 2-3 weeks | — |
| Automatic API Documentation | Manual setup required | Yes (OpenAPI 3.0) |
| Type Hint Support | Optional | Full (enforced) |
Show 9 more attributesAuto Documentation Generation Manual (requires Flask-RESTX, Flasgger) Automatic (Swagger UI + ReDoc) Time to 'Hello World' App(lines of code) 4-5 lines 8-10 lines Type Safety Support Native (Python type hints) — Built-in Documentation Generation Automatic (Swagger UI + ReDoc) — Built-in Request Validation Yes (Pydantic) — Time to Hello World API(minutes) ~5 minutes — Built-in Validation Framework Pydantic (integrated) — Time to Production Hello World(minutes) 5 minutes — Built-in Features Count(features) 12 core features — | ||
| GitHub Stars(stars) | ~95,000 stars(winner) | ~80,000 stars |
| GitHub Stars (as of 2026)(stars) | 68,000+ stars | — |
| Related Packages (PyPI)(packages) | ~8,500(winner) | ~2,100 |
| Package Ecosystem Size(available packages) | 300,000+ (PyPI) | 500,000+ (PyPI)(winner) |
| Available Extensions(count (approx.)) | 2,500+ | — |
| Available Extensions/Packages(count) | 15,000+ packages | — |
| Ecosystem Extensions(packages) | 5,000+ | — |
Show 10 more attributesAvailable Packages/Gems(count) 500,000+ — Third-Party Extensions(extensions) 800+ — Available Packages/Modules(count) ~150,000+ PyPI packages — ML/Data Science Library Support(text) Native: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch — Third-party Packages(packages) 2,000+ packages — Python/Go Package Ecosystem Size(packages) 400,000+ — Ecosystem Size (package repositories)(packages) ~480,000 packages (PyPI) — Community Library Ecosystem(total packages) 500,000+ PyPI packages (Python ecosystem) — Ecosystem Size (Packages)(packages) ~350,000 PyPI packages (FastAPI-specific: ~4,000) — Available Packages/Libraries(count) ~500,000 (PyPI) — | ||
| Minimum Python Version(version) | Python 2.7+ (legacy) / 3.4+ | Python 3.6+ |
| Minimum Python/Node Version | Python 3.7+ | — |
| Time to First API Endpoint(minutes) | 7 minutes | ~5 minutes(winner) |
| Time to Production (Small API)(hours) | 4-8 | — |
| Time to Basic API (Hello World)(lines of code) | ~5 lines | — |
| Memory Usage (Idle)(MB) | ~35 MB per instance(winner) | 50-100MB |
| Idle Memory Usage(MB) | 50-80 | — |
| Memory Usage (Hello World)(megabytes) | ~40 MB | — |
| Cold Start Time (Serverless)(ms) | ~450 ms | — |
| Concurrent Connection Limit (Practical)(connections) | 500 optimal | — |
| GitHub Stars (Community)(stars) | 68,000+ stars | — |
| Active Contributors(developers) | 2,500+ | — |
| GitHub Stars (Popularity Proxy)(stars) | ~67,000 stars | — |
| GitHub Stars (2026)(stars) | 75,000+ | — |
| Minimum Project Boilerplate(lines of code) | 5-7 lines | — |
| Learning Curve for Beginners(hours to proficiency) | 20-30 hours | — |
| Market Share Among Web Frameworks(percent) | 70% (Python) | — |
| Production Deployments(organizations) | ~2.5M active(winner) | ~400K active |
| Production Deployments (Estimated)(count) | 2.5M+ | — |
| PyPI Weekly Downloads(downloads) | ~2.8M (Jan 2026) | — |
| Production Applications (market estimate)(thousands) | 45,000+ apps | — |
Show 1 more attributeNPM/PyPI Weekly Downloads(weekly downloads) ~2.8M (PyPI/month) — | ||
| Memory Usage (Single Instance)(MB) | 75 MB | — |
| Memory Usage per Process(MB) | ~40 MB | — |
| Minimum Memory Footprint(GB) | 40MB | — |
| Job Postings (Global, 2025)(jobs) | 23,500 positions | — |
| Production Deployments (Est.)(years in market) | 12+ years | — |
| Initial Release Year(year) | 2010(winner) | 2018 |
| Framework Age(years) | 6 years (2018) | — |
| Time to Build First App(hours) | ~2 hours | — |
| Stack Overflow Questions(count (thousands)) | 40,000+(winner) | ~30,000 questions |
| Third-Party Extensions Available(plugins) | 10,000+ extensions(winner) | ~2,500 extensions |
| Time to Basic Productivity(hours) | 2-4 hours(winner) | 4-8 hours |
| Global Job Openings (2024)(positions) | 45,000+ | — |
| Built-in Request/Response Handling | Yes (Werkzeug-based) | — |
| Average Community Response Time (GitHub Issues)(hours) | 24-36 hours | — |
| Concurrency Model | Synchronous (WSGI) | — |
| Async Support | Requires Flask-APScheduler or manual async setup | Native async/await built-in |
| Native Async Support | Native (async/await throughout) | — |
| Built-in Dependency Injection(feature availability) | Manual setup required | — |
| Async Support Quality | Native async/await with asyncio | — |
Show 1 more attributeFramework Type High-level API framework (built on Starlette) — | ||
| Package Size(MB) | ~2.5 MB(winner) | ~100 KB |
| Default Dependencies(count) | 1 (werkzeug)(winner) | 6 (starlette, pydantic, etc.) |
| Learning Curve Difficulty | Easy (1.5/5)(winner) | Moderate (3.5/5) |
| Time to First Hello World(lines of code) | 4 lines | — |
| Learning Curve(hours) | 30-40 hours | — |
| Deployment Without Extra Server(text) | No - requires WSGI server (Gunicorn, uWSGI) | — |
| Production Adoption Rate(percent) | 22% (Stack Overflow 2024) | — |
| First Release Year | 2018 | — |
| Deployment Model(type) | Requires app server (Uvicorn) | — |
| Python Version Support(versions) | 3.7+ | — |
| Async-First Support | Native, default behavior | — |
| Core Library Size(kilobytes) | 1,200KB (with uvicorn) | — |
| Production Maturity(years) | 7 years | — |
| Job Market Postings (2026)(active positions) | ~12,000 positions | — |
| Framework Maturity(years) | 6 years (released 2018) | — |
| Active Job Listings (2025)(positions) | 42,000 | — |
| Production Readiness Without External Server | Requires ASGI (Uvicorn) | — |
FFlask
FFastAPI
Core Framework Size(MB)
~11 KB
—
Request/Response Latency (simple GET)(ms)
25-35 ms
—
Startup Time(milliseconds)
~150ms
250-500ms
Framework Core Size(KB)
~150 KB
—
Average Startup Time(seconds)
~500 ms
—
Show 23 more attributes
Requests Per Second (Concurrent Load)(RPS)
~2,500 RPS
—
Requests Per Second (Benchmark)(req/s)
~1,200 req/s
—
Throughput (Requests Per Second)(req/s)
~2,100 req/s
~32,000 req/s
Throughput (Requests/Second)(req/s)
400-600
8,000-12,000
Requests Per Second (Throughput)(req/s)
~7,500 req/s
~22,000 req/s
Cold Start Time(milliseconds)
~150ms
300ms
Memory Usage (Baseline)(MB)
~30MB
—
Memory Usage (base)(MB)
~10MB
—
Latency (p99 response time)(ms)
8-12 ms
—
Framework Requests Per Second(req/s)
10,000
—
Average Latency (Hello World)(ms)
~85 ms
—
Throughput Performance(requests/second)
~15,000 req/s
—
Throughput Benchmark (requests/sec)(req/s)
~18,000 req/s
—
Performance - Request Throughput(requests/sec)
~15,000-18,000 req/sec
—
Request Throughput(requests/second)
~12,000 req/s
—
Cold Start Latency(milliseconds)
300ms
—
P99 Latency (typical)(ms)
150-250
—
Peak Throughput (Req/s)(requests per second)
~10,000 req/s
—
Memory Usage (Idle Instance)(MB)
~80-120 MB
—
Requests Per Second (Single Instance)(req/s)
~7,500 req/s
—
Memory Footprint Per Process(MB)
~15 MB
—
Application Startup Time(seconds)
150ms (average)
—
Requests Per Second (1KB payload)(req/s)
~28,000
—
Built-in Database ORM(feature)
None (use SQLAlchemy separately)
—
Admin Interface
Requires manual or third-party setup
—
Native Async/Await Support
Experimental in Flask 2.0+
Native first-class support
Built-in Data Validation
No (manual or extension-based)
Yes (Pydantic integration)
WebSocket Support
No (requires Flask-SocketIO)
—
Show 12 more attributes
Data Science Library Integration
Native (NumPy, TensorFlow, Pandas)
—
Built-in ORM Support
Via SQLAlchemy extension
—
Built-in Admin Dashboard
No, requires build
—
Async Request Support
Full native support
—
Auto API Documentation
Native (Swagger UI + ReDoc built-in)
—
Built-in ORM
No (requires external library)
—
Auto-generated API Documentation
Yes (automatic)
—
Built-in API Documentation
Yes (Swagger UI + ReDoc automatic)
—
Native Type Validation
Yes (Pydantic built-in)
—
Built-in Authentication
No (requires FastAPI-Users, python-jose)
—
Database ORM Included
No (requires SQLAlchemy, Tortoise-ORM)
—
Auto-Generated API Docs
Yes (Swagger/ReDoc)
—
Weekly Downloads (PyPI)(thousands)
850 thousand
—
Weekly npm Downloads(downloads)
~1.2M (PyPI: ~2.8M)
—
Weekly Package Downloads(millions)
~450,000 (PyPI)
—
NPM Weekly Downloads(downloads)
2.5M weekly
—
Minimal Project Setup Time(minutes)
5-10
—
Minimum Code Boilerplate (Hello World)(lines)
12 lines
—
Setup Time to First Running App(minutes)
8-12 minutes
—
Time to Build Basic CRUD App(minutes)
3.5 hours (manual setup required)
—
Lines of Code for Basic Endpoint(lines)
5-8 lines
—
Stack Overflow Questions (all-time)
1,200 thousand
—
Authentication Built-in
No (use Flask-Login or similar)
—
Auto-Documentation Support
Manual integration required
Built-in (OpenAPI 3.0)
Time to 'Hello World'(minutes)
3 minutes
—
Recommended Learning Duration(weeks)
2-3 weeks
—
Automatic API Documentation
Manual setup required
Yes (OpenAPI 3.0)
Type Hint Support
Optional
Full (enforced)
Show 9 more attributes
Auto Documentation Generation
Manual (requires Flask-RESTX, Flasgger)
Automatic (Swagger UI + ReDoc)
Time to 'Hello World' App(lines of code)
4-5 lines
8-10 lines
Type Safety Support
Native (Python type hints)
—
Built-in Documentation Generation
Automatic (Swagger UI + ReDoc)
—
Built-in Request Validation
Yes (Pydantic)
—
Time to Hello World API(minutes)
~5 minutes
—
Built-in Validation Framework
Pydantic (integrated)
—
Time to Production Hello World(minutes)
5 minutes
—
Built-in Features Count(features)
12 core features
—
GitHub Stars(stars)
~95,000 stars
~80,000 stars
GitHub Stars (as of 2026)(stars)
68,000+ stars
—
Related Packages (PyPI)(packages)
~8,500
~2,100
Package Ecosystem Size(available packages)
300,000+ (PyPI)
500,000+ (PyPI)
Available Extensions(count (approx.))
2,500+
—
Available Extensions/Packages(count)
15,000+ packages
—
Ecosystem Extensions(packages)
5,000+
—
Show 10 more attributes
Available Packages/Gems(count)
500,000+
—
Third-Party Extensions(extensions)
800+
—
Available Packages/Modules(count)
~150,000+ PyPI packages
—
ML/Data Science Library Support(text)
Native: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch
—
Third-party Packages(packages)
2,000+ packages
—
Python/Go Package Ecosystem Size(packages)
400,000+
—
Ecosystem Size (package repositories)(packages)
~480,000 packages (PyPI)
—
Community Library Ecosystem(total packages)
500,000+ PyPI packages (Python ecosystem)
—
Ecosystem Size (Packages)(packages)
~350,000 PyPI packages (FastAPI-specific: ~4,000)
—
Available Packages/Libraries(count)
~500,000 (PyPI)
—
Minimum Python Version(version)
Python 2.7+ (legacy) / 3.4+
Python 3.6+
Minimum Python/Node Version
Python 3.7+
—
Time to First API Endpoint(minutes)
7 minutes
~5 minutes
Time to Production (Small API)(hours)
4-8
—
Time to Basic API (Hello World)(lines of code)
~5 lines
—
Memory Usage (Idle)(MB)
~35 MB per instance
50-100MB
Idle Memory Usage(MB)
50-80
—
Memory Usage (Hello World)(megabytes)
~40 MB
—
Cold Start Time (Serverless)(ms)
~450 ms
—
Concurrent Connection Limit (Practical)(connections)
500 optimal
—
GitHub Stars (Community)(stars)
68,000+ stars
—
Active Contributors(developers)
2,500+
—
GitHub Stars (Popularity Proxy)(stars)
~67,000 stars
—
GitHub Stars (2026)(stars)
75,000+
—
Minimum Project Boilerplate(lines of code)
5-7 lines
—
Learning Curve for Beginners(hours to proficiency)
20-30 hours
—
Market Share Among Web Frameworks(percent)
70% (Python)
—
Production Deployments(organizations)
~2.5M active
~400K active
Production Deployments (Estimated)(count)
2.5M+
—
PyPI Weekly Downloads(downloads)
~2.8M (Jan 2026)
—
Production Applications (market estimate)(thousands)
45,000+ apps
—
Show 1 more attribute
NPM/PyPI Weekly Downloads(weekly downloads)
~2.8M (PyPI/month)
—
Memory Usage (Single Instance)(MB)
75 MB
—
Memory Usage per Process(MB)
~40 MB
—
Minimum Memory Footprint(GB)
40MB
—
Job Postings (Global, 2025)(jobs)
23,500 positions
—
Production Deployments (Est.)(years in market)
12+ years
—
Initial Release Year(year)
2010
2018
Framework Age(years)
6 years (2018)
—
Time to Build First App(hours)
~2 hours
—
Stack Overflow Questions(count (thousands))
40,000+
~30,000 questions
Third-Party Extensions Available(plugins)
10,000+ extensions
~2,500 extensions
Time to Basic Productivity(hours)
2-4 hours
4-8 hours
Global Job Openings (2024)(positions)
45,000+
—
Built-in Request/Response Handling
Yes (Werkzeug-based)
—
Average Community Response Time (GitHub Issues)(hours)
24-36 hours
—
Concurrency Model
Synchronous (WSGI)
—
Async Support
Requires Flask-APScheduler or manual async setup
Native async/await built-in
Native Async Support
Native (async/await throughout)
—
Built-in Dependency Injection(feature availability)
Manual setup required
—
Async Support Quality
Native async/await with asyncio
—
Show 1 more attribute
Framework Type
High-level API framework (built on Starlette)
—
Package Size(MB)
~2.5 MB
~100 KB
Default Dependencies(count)
1 (werkzeug)
6 (starlette, pydantic, etc.)
Learning Curve Difficulty
Easy (1.5/5)
Moderate (3.5/5)
Time to First Hello World(lines of code)
4 lines
—
Learning Curve(hours)
30-40 hours
—
Deployment Without Extra Server(text)
No - requires WSGI server (Gunicorn, uWSGI)
—
Production Adoption Rate(percent)
22% (Stack Overflow 2024)
—
First Release Year
2018
—
Deployment Model(type)
Requires app server (Uvicorn)
—
Python Version Support(versions)
3.7+
—
Async-First Support
Native, default behavior
—
Core Library Size(kilobytes)
1,200KB (with uvicorn)
—
Production Maturity(years)
7 years
—
Job Market Postings (2026)(active positions)
~12,000 positions
—
Framework Maturity(years)
6 years (released 2018)
—
Active Job Listings (2025)(positions)
42,000
—
Production Readiness Without External Server
Requires ASGI (Uvicorn)
—
Pros & Cons
10 pros·6 cons across both
F
F
F
Flask
+5-3
Pros
- Minimal learning curve with small core API (~10 core concepts)
- Extremely lightweight with zero required dependencies for basic apps
- Massive ecosystem: 1000+ third-party extensions available
- 15+ years of production battle-testing across millions of applications
- Flexibility to choose and integrate any tools (ORM, validation, auth)
Cons
- No built-in async support (requires Flask-APScheduler or external async libraries)
- Manual setup needed for API documentation, data validation, and OpenAPI schemas
- Significantly slower throughput (~7,500 req/s vs FastAPI's ~22,000 req/s)
F
FastAPI
+5-3
Pros
- Native async/await support enabling concurrent request handling by default
- Automatic OpenAPI/Swagger UI and ReDoc documentation generation
- Built-in Pydantic data validation with automatic error responses
- ~3x higher throughput than Flask (22,000+ req/s in benchmarks)
- Type hints enable IDE autocomplete, type checking, and better developer experience
Cons
- Smaller, younger community (50% fewer Stack Overflow answers than Flask)
- Requires understanding of async concepts for experienced developers
- Fewer third-party integrations compared to Flask's mature ecosystem
Frequently Asked Questions
5 questions
For simple CRUD APIs or monolithic applications, Flask remains excellent. For microservices, real-time features, or APIs requiring high concurrency, FastAPI is the better choice. FastAPI's growth rate (2,000+ stars/month) suggests it's becoming the modern standard for new Python APIs, but Flask's maturity makes it reliable for production at any scale.
Resources & Learn More
Curated sources to dive deeper
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