Fly.io vs Railway
Fly bills you for the VM you reserved, whether you use it or not. Railway bills you for what you actually consumed, down to the second. That one difference changes how each platform feels for anything that isn't running flat out.
Pick Railway if your workload is bursty or low-traffic and you'd rather pay for actual usage than a reserved VM. Stay on Fly if you're running something that needs to be always-on anyway, where per-second billing doesn't save you much.
Side by side
Fly.io vs Railway at a glance
| Fly.io | Railway | |
|---|---|---|
| Billing unit | Per-VM, metered by the hour | Per-second, actual CPU/memory/volume usage |
| Free plan | None for new signups since Oct 2024 | One-time $5 trial credit, no card required |
| Entry paid tier | ~$2/mo smallest Machine, often $8–12 all-in | Hobby $5/mo, Pro $20/mo per seat |
| Deploy unit | Firecracker microVM (Machine) | Managed container, from repo or Dockerfile |
| Cold start | None, always-on by default | None, billed per second either way |
| Idle cost | Still billed for reserved capacity | Close to $0 when actually idle |
| Scaling & regions | Manual, via CLI | Managed, less manual tuning needed |
| Best for | Always-on, region-pinned workloads | Bursty or low-traffic container apps |
Sources: Fly.io pricing · Railway pricing. Compiled July 2026.
Where Railway wins
You only pay for what actually ran
Railway's published rates meter memory, CPU, volumes and egress separately, all by consumption rather than a flat reserved rate. For a workload that spikes occasionally and sits quiet the rest of the time, that adds up to a noticeably smaller bill than a reserved Fly Machine that's paid for around the clock either way.
The container layer is someone else's problem
Deploy from a repo or Dockerfile and Railway handles the orchestration underneath it, the same broad tradeoff Render makes against Fly's more exposed Machine model. You lose some of Fly's direct control over exactly where and how the workload runs, in exchange for not having to manage it.
Where Fly.io still wins
Once a workload is genuinely always-on and running at steady load, per-second billing stops being an advantage since you're paying for close to 100% utilization either way. Fly's direct Machine access also still wins if you need to pin a workload to a specific region or manage sizing more precisely than Railway's abstraction allows.
Railway is also worth checking against its own history: it killed its original generous free tier in 2023 after abuse from crypto miners, the same kind of platform-level policy shift that pushed people off Fly's free tier later. Nothing stops that from happening again on any platform, including whichever one you migrate to.
Migrating Fly.io → Railway
The path most teams take:
1. Inventory first. List Fly Machines, regions and any `fly.toml` settings around scaling or health checks that Railway configures differently.
2. Connect the repo. Railway deploys straight from a GitHub repo or a Dockerfile; set up the same environment variables and secrets in its dashboard.
3. Run both for one cycle. Compare actual Railway usage-based billing against your current Fly bill for a real workload before fully committing, since per-second pricing is harder to estimate up front than a flat VM rate.
4. What does not move. Fly volume data needs an explicit export; Railway's own volumes start empty and need the data written back in.
Common questions
FAQ: Fly.io vs Railway
Does Railway still have a free tier?
Not an ongoing one. Railway offers a one-time $5 trial credit with no card required, then moves you to Hobby at $5/mo or Pro at $20/mo per seat. It killed its original recurring free plan back in 2023 after abuse from crypto miners and bots, similar to what pushed Fly to end its own free tier later.
Is Railway's per-second billing actually cheaper than Fly.io?
For workloads that sit idle a lot of the time, usually yes, since you're billed for memory and CPU actually consumed rather than a reserved VM. For workloads running flat out around the clock, the gap narrows and it's worth pricing both out directly for your specific usage.
What's the underlying architecture difference between Fly.io and Railway?
Fly runs each app as a Firecracker microVM that you manage directly by region and size. Railway deploys from a repo or Dockerfile as a managed container and handles the underlying orchestration for you, closer to Render's model than to Fly's.