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Fly.io vs Zeabur

Fly.io scores higher on the AgentReady, 53/100 against 46/100. They differ on 7 of the 41 signals. Which ones decides whether an agent can adopt them without a person watching.

What each one is

Fly.io. Fly.io provides real hardware-isolated Linux computers (called Sprites and Machines) for agents, evals, and tools, with a pay-as-you-go model where billing goes to zero when not in use.

Zeabur. Zeabur is a platform that helps you deploy your service with one click, no matter what programming language or framework you use.

Where Fly.io is ahead

Fly.io passes llms.txt published and mcp discoverable, and Zeabur does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds adopt: mcp integration available. Zeabur misses it.

And on operate, agent compatibility verified. Zeabur misses it.

Where Zeabur is ahead

Zeabur passes clear product positioning, and Fly.io does not. That is discover, whether an agent can find the product at all without being told it exists.

It also holds understand: limits / constraints documented. Fly.io misses it.

And on adopt, free trial or free allowance. Fly.io misses it.

What neither does

Both fail llms-full.txt / full agent docs, structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, no mandatory sales call, agent-compatible signup flow, programmatic credential creation, fast time to first request, copyable quickstart, structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable. If your agent needs any of those, you will be building it yourself either way.

Score, pillar by pillar

The AgentReady splits into four pillars, scored separately, because a product can be easy to find and still impossible to adopt.

Discover. Fly.io leads 80 to 73. Fly.io misses clear product positioning, llms-full.txt / full agent docs; Zeabur misses llms.txt published, llms-full.txt / full agent docs, mcp discoverable.

Understand. Zeabur leads 31 to 23. Fly.io misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented, limits / constraints documented; Zeabur misses structured api reference, openapi / spec quality, authentication documented, request examples provided, response examples provided, errors and status codes documented.

Adopt. Fly.io leads 55 to 45. Fly.io misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, free trial or free allowance, fast time to first request, copyable quickstart; Zeabur misses no mandatory sales call, agent-compatible signup flow, programmatic credential creation, fast time to first request, copyable quickstart, mcp integration available.

Operate is whether an agent can run against it in production and recover when a call fails. Fly.io leads 53 to 35. Fly.io misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable; Zeabur misses structured, predictable output, machine-readable errors, retry behavior documented, idempotency support, rate-limit behavior predictable, agent compatibility verified.

Pricing

Fly.io starts at $29/mo. Zeabur starts at $0/mo and has a free tier.

Signal by signal

Which to pick

Fly.io clears more of the signals an agent needs, so it is the safer default for unattended use. Full profiles: Fly.io and Zeabur. Alternatives to each: Fly.io, Zeabur.

An agent can fetch this as data: POST /v1/compare {"slugs": ["fly", "zeabur"]}