I get asked this a lot, usually as if there's a right answer: Laravel or FastAPI? The honest answer is it depends on what the product needs — and after years of shipping both in production, I've landed on a fairly simple decision process instead of a favorite.
What each one is actually good at
Laravel is a full, opinionated web framework. It comes with an ORM (Eloquent), authentication scaffolding, queues, scheduled jobs, mail, file storage abstractions, and a templating engine, all designed to work together out of the box. If a project needs a traditional web app — user accounts, an admin panel, payments, content that gets rendered server-side — Laravel gets you there with a fraction of the boilerplate.
FastAPIis a much thinner layer: a fast, async Python web framework built around type hints and automatic request validation. It doesn't ship an ORM or an auth system by default — you bring your own (SQLAlchemy, Pydantic, whatever fits). What it's genuinely excellent at is async I/O and streaming responses, which matters enormously the moment you're calling an LLM API and need to stream tokens back to a client instead of blocking on a multi-second response.
Where Laravel wins
- Client products with an admin panel. Auth, roles, CRUD scaffolding — Laravel gives you 80% of an internal admin tool for free.
- Anything with background jobs and scheduling. Laravel's queue system and task scheduler are mature and simple to reason about.
- Teams that need to move fast without reinventing conventions. Laravel's opinionated structure means less time spent deciding how to organize the app.
The e-commerce site I built during my internship, and a good chunk of the dynamic websites I shipped at STATA IT, were Laravel for exactly this reason — real business logic, real admin needs, real deadlines.
Where FastAPI wins
- LLM-backed features. Streaming a model's response token-by-token to the frontend needs an async framework that doesn't block a worker thread per request.
- High-throughput APIs. Async request handling means a single process can hold far more concurrent connections than a traditional sync PHP/Python setup.
- Anything where request/response shapes need to be strictly typed and self-documenting. FastAPI generates an OpenAPI schema from your Pydantic models automatically — the docs can't drift from the code because they're generated from it.
from fastapi import FastAPI
from fastapi.responses import StreamingResponse
from openai import AsyncOpenAI
app = FastAPI()
client = AsyncOpenAI()
@app.post("/chat")
async def chat(prompt: str):
async def token_stream():
stream = await client.chat.completions.create(
model="gpt-4",
messages=[{"role": "user", "content": prompt}],
stream=True,
)
async for chunk in stream:
if chunk.choices[0].delta.content:
yield chunk.choices[0].delta.content
return StreamingResponse(token_stream(), media_type="text/plain")That endpoint streams tokens to the client as the model generates them, instead of making the user stare at a spinner for four seconds and then dump the whole response at once. This is the exact pattern behind most of the LLM features I've shipped, and it's meaningfully harder to do cleanly in a synchronous framework.
The decision, in practice
My actual heuristic, after shipping both: if the product is fundamentally a web application — users, accounts, content, payments, an admin dashboard — I reach for Laravel and get to a working v1 faster. If the product is fundamentally an API — especially one wrapping LLM calls, doing heavy async I/O, or needing strict request/response contracts for a separate frontend team — I reach for FastAPI.
They're not mutually exclusive within a single company, either. It's common for me to have a Laravel app handling the core product — auth, billing, the admin panel — with a FastAPI service running alongside it purely for AI features, communicating over a simple internal API. Each framework does the part it's actually good at.
What I wouldn't do
I wouldn't force FastAPI onto a project that's 90% CRUD and admin screens just because it's newer — you'll end up rebuilding half of what Laravel gives you for free. And I wouldn't force Laravel onto a service that's fundamentally about streaming LLM responses at scale — you'll fight the framework's synchronous defaults the whole way. The framework choice should follow from what the product actually needs to do, not from which one is more fun to write in that week.