Most Bootcamp Grads Pick the Wrong One
Here's the trap: you Google "ML model serving tutorial", find a Flask example, copy-paste it, deploy to Render, and think you're done. Then an interviewer asks "How would you handle 100 concurrent requests?" and you freeze. The problem isn't that Flask is wrong — it's that you never learned why the choice matters.
I've reviewed portfolios from 40+ bootcamp grads this year. About 70% use Flask because that's what the first tutorial showed them. When I ask "Why Flask over FastAPI?", the most common answer is "It was easier to set up." That's not a technical decision — that's inertia.
The real question isn't "Which is better?" It's "What does your choice signal to an interviewer about how you think about production systems?"
The Two-Minute Baseline Test
Before you commit to either framework, run this experiment. It's the fastest way to see what interviewers care about.
Flask version:
python
# flask_serve.py
from flask import Flask, request, jsonify
import torch
import time
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*Continue reading the full article on [TildAlice](https://tildalice.io/fastapi-vs-flask-ml-serving-which-learn-first/)*
