Railway says to pair it with something else for GPUs.
This is that something else — and it's an open market, not another rate card.
The Core Economics
Railway bills usage by the second on the CPU, memory, and egress you actually consume, which is a genuinely better model than fixed tiers. What it doesn't do is set the price by competition. The rate is Railway's rate, on Railway's hardware, and your bill goes up when they say it does.
Akash sets the price by competition. You describe the workload and providers bid for it, so the number moves with supply rather than with one company's margin plan. Prices go down as more providers join instead of up.
Here's what that costs you: nothing you can look up on a rate card. Prices move as providers compete and as more capacity joins the network. See what the market is charging right now on the GPU pricing page.
| Railway | Akash | |
|---|---|---|
| Price | Railway's published usage rates | Set by competitive bids, per deployment |
| Hardware | Railway's infrastructure | A global network of competing providers |
| GPUs | Pair with another platform | Requested in the same deployment file |
| Egress | Metered | Zero |
| Where it runs | Railway's regions | Any provider on the network, or your own hardware |
Architectural Distinctions
One platform for the app and the model
Railway's own guidance is to pair it with a separate service when you need to serve your own weights. That's honest, and it means two platforms, two bills, two failure surfaces, and a network hop between your API and your model. On Akash the GPU service and the web service are two blocks in the same deployment file, bid on together, running under the same lease.
The market prices it, not the vendor
Usage-based billing is still vendor-set billing. On Akash, providers compete for each deployment and you pick the bid. Nobody publishes the number you pay — the market clears it. That's the difference between paying fairly for what you use and paying what competition says it's worth.
You can leave, and take the hardware choice with you
If it runs in Docker, it runs on Akash. Your containers are standard, your deployment file is portable YAML, and the same file deploys to any provider on the network — or to your own hardware, if you run the provider software. No egress fees on the way out. We'd rather earn your business every month than make leaving expensive.
Service Parity Index
| Feature layer | Railway | On Akash | How it works |
|---|---|---|---|
| Compute runtime | Services built from a repo or image | Standard containers | Your image runs directly on provider hardware. |
| Build | Railpack, Nixpacks, or a Dockerfile | Prebuilt images | Build wherever you like. The network needs the image, not your repo. |
| Multi-service apps | Project canvas | One SDL, many services | A single file describes every service, its resources, and its ports. |
| Data persistence | Managed Postgres, MySQL, Redis, Mongo | Persistent volumes, or an outside managed database | Run it as a container with a volume, or point at a managed service. |
| Deployment control | Dashboard, CLI, API | CLI, REST API, MCP, agent skill | An AI coding agent with an API key can deploy, inspect, and close workloads. |
| GPUs | Pair with another platform | Requested in the same SDL | Add a GPU block naming vendor and model to any service. |
What We Are. What We Aren't.
Akash doesn't have a centralized SLA, because we aren't a centralized provider. We're a marketplace. You choose your level of reliability by choosing your provider — Verified Enterprise data centers with redundant power and networking, or Community Independent operators optimized for price.
What Railway sells that we don't: managed databases with backups handled, build-from-repo with PR environments, scale-to-zero on idle, a project canvas that shows your whole topology, and one company to email when something breaks. If that developer experience is the product you're buying, Railway is very good at it. If you want GPUs in the same file as your app and a price the market sets, keep reading.
FAQs
Start Building
Keep the app you've built, add the GPU it's about to need, and let providers compete for both.