Free Python hosting works for a weekend demo, a learning project, or an internal tool that gets hit twice a day. It does not work for a product with real users, a database that needs to survive a redeploy, or a service that needs to wake up within 200ms of a request. The honest list below covers every free tier that matters in 2026, what each one actually gives you, where it breaks, and the cost number that makes “free” stop being the right answer.
I have run Python services on every free tier on this list. I have also been the person who paid the bill when “free” met production traffic. This post is the comparison I wish I had before I picked the cheap option three times in a row.
Table of contents
- The honest answer in two paragraphs
- What “free Python hosting” actually means in 2026
- The free tiers that matter
- Feature comparison table
- The cold start tax most guides skip
- The database gotcha
- When free is the right answer
- The moment to leave free behind
- The cost math: free vs cheap paid
- A migration path that does not require a rewrite
- FAQ
The honest answer in two paragraphs
The free Python hosting tier you should pick depends on what you are building. For a learning project, a CLI, a one-off scraper, or a public demo, every option on this list is good enough. For a product with users, a database that holds anything you cannot lose, or a service that needs to respond in under a second, the free tier is a temporary stepping stone, not a destination.
The reason is not that free tiers are bad. The reason is that free tiers make trade-offs that are wrong for production: cold starts, sleep on inactivity, no always-on database, limited outbound network, hard memory caps, and a support contract that says “we hope you figure it out.” Those trade-offs are fine for a hobby project. They are not fine for a product with paying users, and the moment you accept them as a production constraint, you are spending engineering time on workarounds that a paid tier would have removed.
The rest of this post is the list, the limits, and the cost number that lets you decide when to stop pretending.
What “free Python hosting” actually means in 2026
The phrase covers three very different categories, and most confusion comes from mixing them up:
- Free tier on a commercial PaaS. A real production platform with a free plan that has usage caps. Sleep on inactivity, limited hours, small database. Good for prototypes and small projects.
- Open-source self-hosted on free infrastructure. You run the Python service on free VM credits, free container hours, or your own hardware. The platform is free; the time you spend keeping it up is not.
- Free static + serverless function combo. Static hosting with a serverless function for the Python backend. Works for very small APIs. Hits hard limits at scale.
The first category is what most people mean by “free Python hosting.” The second is the right answer when the free tier is too restrictive and you have the operational maturity to run your own service. The third is a trap dressed as a deal.
The free tiers that matter
This list is current as of 2026. Prices and limits change; double-check before you commit.
RunxBuild free plan
RunxBuild’s free plan is built around the same primitives as the paid plan: services, managed databases, environment variables, custom domains, deploy logs, and one-click Git deploys. The free plan includes a meaningful allowance of monthly runtime and a small managed database, with no forced sleep on low traffic. It is the cleanest path for a Python service that needs to behave like a real product from day one.
The honest list:
- Monthly service runtime included at no charge
- A small managed database
- One-click deploys from Git
- Logs, environment variables, custom domains
- No credit card required to start
The reason to pick it: the free plan is the same product as the paid plan. You do not rewrite your service when you upgrade. You change a plan, you keep the service definition, the environment variables, the database URL, and the domain. The migration is a plan toggle, not a weekend.
For teams that want to know what the upgrade cost is before they need it, the RunxBuild hosting calculator shows the monthly bill for the instance size and traffic pattern that fits a real Python service.
Render free plan
Render’s free plan supports Python web services, background workers, cron jobs, and static sites. The catch most people learn the hard way: free web services spin down after 15 minutes of inactivity. The first request after sleep pays the cold-start cost, which is usually 30-50 seconds. For an internal tool that gets hit twice a day, that is fine. For a customer-facing product, that is a 30-50 second “loading” spinner on every first visit.
Postgres on Render is available as a free trial that ends after 30 days, not as a free plan. There is no always-free managed Postgres on Render as of 2026.
Railway free plan
Railway’s free plan gives a small monthly credit (around $5) and trial-based access to managed services. The free credit is generous for a learning project and runs out fast for a production service. The free trial on managed Postgres also expires, which is the same gotcha as Render: the database is the part that costs money.
Fly.io free plan
Fly.io’s free plan includes a small number of shared-CPU VMs with 256MB RAM and a few GB of persistent volume. The free VMs do not sleep on inactivity the way Render’s free tier does, but they share a CPU and the performance floor is unpredictable. Postgres on Fly is not free for production use.
PythonAnywhere free plan
PythonAnywhere is the longest-running free Python hosting option. The free plan includes one web app on the pythonanywhere.com subdomain, scheduled tasks, and a small amount of disk space. The free plan does not allow outbound network access to arbitrary hosts (only to a whitelist), which breaks most modern Python services that talk to third-party APIs. It is a great environment for learning Django and Flask. It is a poor environment for a modern Python API.
Replit free plan
Replit’s free plan runs Python in a constrained sandbox with limited CPU, limited memory, and the project always on. The Replit free plan is good for collaborative development and quick demos. It is not a production hosting target. The “Always On” feature is paid, and without it the project spins down between sessions.
Vercel serverless functions
Vercel is a great static host. The serverless function tier for Python works for tiny APIs that respond in a few hundred milliseconds and do not hold connections open. The free tier is generous for hobby projects. The moment you need a long-running worker, a websocket, or a connection pool to a database, serverless functions stop being the right tool.
Netlify functions
Same trade-off as Vercel. Free Python functions are limited in execution time and memory. The hosting is great for static sites. The backend story is “this works for a contact form, not for a product.”
Google Cloud Run free tier
Cloud Run has a generous free tier (2 million requests per month) and the request-based pricing model is honest. The catch is that the free tier is for invocation count and CPU-seconds, not for always-on services. A low-traffic service is cheap. An always-on service is not free, and the database (Cloud SQL) is never free.
AWS Lambda free tier
Same model as Cloud Run. 1 million free requests per month, then per-request pricing. Cold starts are the predictable complaint. The database is never free.
Feature comparison table
| Platform | Free Python service | Sleep on inactivity | Managed DB free | Custom domain free | Outbound network |
|---|---|---|---|---|---|
| RunxBuild | Yes | No | Small free managed DB | Yes | Yes |
| Render | Yes | Yes (15 min) | 30-day trial only | Yes | Yes |
| Railway | Credit-based | No | Trial only | Yes | Yes |
| Fly.io | Yes (shared CPU) | No | No | Yes | Yes |
| PythonAnywhere | Yes (1 app) | No | SQLite only | No (paid) | Whitelist only |
| Replit | Yes (constrained) | Yes (without Always On) | Replit DB only | Yes | Yes |
| Vercel functions | Yes (serverless) | N/A | No (use external) | Yes | Yes |
| Netlify functions | Yes (serverless) | N/A | No (use external) | Yes | Yes |
| Cloud Run | Yes (request-based) | Cold start | No (Cloud SQL) | Yes | Yes |
| AWS Lambda | Yes (request-based) | Cold start | No (RDS) | Yes | Yes |
The “Sleep on inactivity” column is the one that matters for most products. A free tier that sleeps is free until the first user comes back from lunch and waits 30 seconds for the page to load. The cost of that 30-second wait is a user who closes the tab.
The cold start tax most guides skip
Cold starts are the silent bill on every serverless and free-tier plan. The cost is real even when the dollar amount is zero.
For the user: A 5-30 second wait on the first request after a period of inactivity. Most users blame the product, not the platform.
For the platform: A wake-up cycle that consumes more CPU and memory than a warm request, which counts against the free tier’s CPU-second budget.
For the engineer: A debugging session that ends with “it works on my machine” because the engineer never lets the service sleep.
For the on-call rotation: A spike in 5xx errors every Monday morning as the free-tier services wake up to handle the weekend’s queued webhooks.
The fix is not “wake the service more often.” The fix is to pick a tier that does not sleep. For most products, that means a small paid instance or a free tier that does not impose sleep (RunxBuild, Fly.io shared CPU, Railway credit-based). For a small set of products, the serverless model is genuinely the right answer — short-lived requests, spiky traffic, no always-on database.
The database gotcha
The free Python service is rarely the expensive part. The database is.
Most free tiers include the service, not the database. The database is a separate line item that starts as a free trial and ends as a paid plan. The migration from “free” to “the database suddenly costs $15/month” is the most common surprise in the first 90 days of a new project.
The exceptions:
- RunxBuild free plan includes a small managed database. The plan and the database grow together.
- PythonAnywhere includes SQLite only. The free plan has no managed Postgres.
- Supabase, Neon, PlanetScale are database-only free tiers that pair with any compute platform. If you are using a serverless function or a free Python service, these are the standard way to get a free database.
The right pattern for a real product: pick the compute tier and the database tier together. The free compute plus a paid managed database is fine. The free compute plus a free trial database is a 30-day clock.
For cost modeling across both, the RunxBuild hosting calculator shows the database line item separately from the service line item, which is the right way to think about it.
When free is the right answer
Free Python hosting is the right answer when:
- You are learning Python, Django, or FastAPI and the deploy path is part of the lesson.
- You are building a portfolio piece, a demo, or a CLI that exposes a public endpoint.
- You are running an internal tool that gets hit a few times a day and can survive a 30-second cold start.
- You are prototyping a product idea and the next 30 days are about validation, not scale.
- You are running a webhook receiver for personal projects and the upstream service tolerates retries.
Free is also the right answer when the alternative is “do not build the thing.” The best Python service is the one that exists. The platform it runs on is secondary to the product it powers.
The moment to leave free behind
The free tier is a temporary state. The moment to leave is when one of the following becomes true:
- You have users who notice the cold start. If support is getting “the site is slow” tickets, the free tier is costing you trust.
- The database has anything you cannot lose. The free-tier database usually has weaker backup guarantees. A customer table, a payment history, or a list of users is a “do not lose this” responsibility.
- The outbound network is restrictive. Most free tiers allow outbound. PythonAnywhere’s free plan does not. If you need to call a third-party API, this is a hard constraint.
- You need a custom domain. Some free tiers allow it, some do not. A product on a free subdomain signals “hobby project” to most visitors.
- You need environment variables for secrets. Most free tiers support env vars, but the secret management story (rotation, audit, scoped access) is usually a paid feature.
- You need log retention beyond a few days. Free tiers usually have a small log window. The first time you need to debug a bug from last Tuesday, you will feel this gap.
- You need to scale beyond one instance. Free tiers are usually single-instance. The first time you need to run a second worker or a queue, you are on a paid plan.
If three or more of these are true, the free tier is a tax on your engineering time. The right move is to pay for the smallest instance that solves the problem and stop thinking about the platform.
The cost math: free vs cheap paid
For a small Python service with light traffic, the realistic monthly bills are:
- RunxBuild free plan: $0 with usage caps, $5-7/month on the smallest paid tier
- Render: $0 (free service) + $7/month for the smallest Postgres
- Railway: $5/month credit + usage overage
- Fly.io: $0 (free shared VMs) + $2-5/month for the smallest Postgres
- PythonAnywhere: $0 (free plan) or $5/month for Hacker plan
- Cloud Run: $0-2/month for low traffic + $7-10/month for Cloud SQL
- Vercel functions + Neon DB: $0 for both, with hard limits
The break-even point is usually around month 2 or 3. By that point, the team has either validated the product and needs real infrastructure, or pivoted and is not paying for anything.
For teams that want to know the exact number for their workload, the RunxBuild hosting calculator shows the monthly cost for a Python service, a managed database, and a small storage bucket. It is a useful check before you commit to a plan.
A migration path that does not require a rewrite
The mistake most teams make is to write the project against the specific quirks of the free tier, then hit a hard wall when they need to upgrade. The right pattern is:
- Use a
requirements.txtorpyproject.toml. Neverpip installinto the deploy environment. The dependency file is the contract that survives every platform change. - Use environment variables for configuration. Database URL, API keys, host, port. Never hardcode. The 12-factor pattern is the cheapest insurance you will ever buy.
- Use a managed database from day one. Even a free-tier one. SQLite is fine for development, but a managed database gives you backups, connections, and observability that the embedded file does not.
- Use a standard Dockerfile or buildpack. The
python:3.12-slimimage, thepip install -r requirements.txtbuild command, and theuvicorn main:app --host 0.0.0.0 --port $PORTstart command work on every platform on this list. If a platform requires a non-standard setup, that is a signal to pick a different platform. - Use logs and health checks. A
/healthzendpoint that returns 200 when the service is up. Structured logs that can be searched. These are the operational primitives that survive every platform change.
With those in place, a platform migration is a 30-minute job: build a new service, copy the env vars, point the DNS, decommission the old service. The application code does not change.
For Python service hosting specifically, the RunxBuild Python service docs walk through the standard service shape: a Python runtime, a dependency file, a start command, environment variables, a health check, and a managed database. The same pattern works on Render, Railway, Fly, or any other PaaS.
FAQ
What is the best free Python hosting in 2026?
For a learning project or a portfolio piece, PythonAnywhere is the most established free tier. For a service that behaves like a real product on day one, RunxBuild’s free plan is the cleanest path. For a serverless API, Vercel or Netlify functions are the standard. The “best” answer depends on whether you are learning or shipping.
Is free Python hosting really free?
The service usually is. The database usually is not. The hidden cost is the engineering time spent working around the limits of the free tier. The honest accounting: $0 in platform fees, $X in engineering time, where $X depends on the limits of the free tier and how often you hit them.
Can I host a Flask or FastAPI app for free?
Yes. Flask, FastAPI, Django, Bottle, Pyramid, and Starlette all run on every free tier on this list. The choice of framework does not change the hosting options.
Do free tiers support custom domains?
Most do, with a small caveat: the free tier usually gives you a branded subdomain (yourapp.runxbuild.com, yourapp.onrender.com) plus the option to attach a custom domain. The custom domain requires DNS configuration on your registrar. The free tier does not include a domain registration.
Can I run a database on a free Python hosting tier?
It depends on the platform. RunxBuild’s free plan includes a small managed database. Render, Railway, and Fly.io do not include a free managed database as of 2026. Serverless platforms (Vercel, Netlify) require an external database. Pair them with a free-tier managed database from Supabase, Neon, or PlanetScale.
Will my free Python service sleep or cold start?
On Render, yes, after 15 minutes of inactivity. On serverless platforms (Vercel, Netlify, Cloud Run, Lambda), the service cold-starts on the first request after a quiet period. On RunxBuild, Fly.io shared VMs, Railway credit-based, and PythonAnywhere, the service stays warm. The cold-start cost is 5-30 seconds, which is the difference between a usable product and a hobby project.
How do I migrate from a free tier to a paid tier?
If you used a dependency file, environment variables, a managed database, and a standard build/start command, the migration is a 30-minute job: create the new service, copy the env vars, point the domain, decommission the old service. The application code does not change. If you used platform-specific quirks (Render’s auto-detect, Heroku’s buildpacks), the migration is longer.
Is there a free Python hosting option with no sleep and no credit card?
RunxBuild’s free plan and Fly.io’s free VMs both fit. Both let you sign up without a credit card and run a small Python service without a forced sleep on inactivity. The catch is the resource caps, which are real but reasonable for a small project.
What is the cheapest way to host a Python API in production?
For a small service, the cheapest realistic option is a small instance on a PaaS plus a managed database. The all-in number is usually $5-15/month, depending on the platform and the database size. The RunxBuild hosting calculator shows the exact number for a specific instance size and traffic pattern.
Should I host my Python app on free tier or pay from day one?
Pay from day one if the product has users. The engineering time you save by not working around the free tier’s limits is usually more valuable than the $5-15/month you would have spent on a paid tier. Free tier if the product is a prototype, a learning project, or an internal tool that is not on the critical path.