Vercel vs. Fly.io

As AI technology advances, choosing the right platform is crucial for your team's speed, governance, and long-term success. Both Vercel and Fly.io have their strengths. The sections below compare them across developer experience, scalability, and total cost of ownership.

As AI technologies evolve, delivering and scaling applications has become essential for powering modern businesses, from AI startups to large-scale enterprises. There are various solutions available, including comprehensive cloud operating systems, managed Platform-as-a-Service (PaaS), and traditional IaaS. Selecting the right platform is crucial for your team's velocity, governance, and long-term success.

Vercel and Fly.io both bring unique strengths to application delivery, each with its own capabilities and limitations. The best choice depends on your specific use case and requirements. In the following sections, we'll compare both platforms regarding developer experience, scalability, and total cost of ownership, helping you determine the most suitable option for your needs—even if it's not us.

Vercel vs. Fly.io at a Glance

Feature	Vercel	Fly.io
Infrastructure	Proprietary Edge/Serverless Platform	Edge micro-VMs (Firecracker)
Source Available
Deployment Options	Cloud only	Cloud only
Free Trial	Hobby free tier (4 Active CPU hrs + 360GB-hrs memory)	Free allowance (shared CPU, limited)
Max vCPU per Service	Default 1 vCPU/function (Fluid Compute for more)	Plan-based (per VM size)
Max RAM per Service	Default 2GB; higher via Fluid Compute	Plan-based (per VM size)
Custom Domains	Hobby: 50/project; Pro: higher limits
Replicas per Service	Auto-scaled instances (no manual replica caps)	(within org limits)
Cron Jobs	Hobby: 2/day; Pro: 40/account (20/project)	Scheduled machines
Log Retention	Short-term logs; up to 30d with Observability Plus	Limited (plan-based)
Scale-to-Zero		(saves on idle)
App Marketplace

Cost evidence

Monthly Cost Examples: Plans vs. Usage Billing

Estimates use the listed average CPU and RAM for a 30-day month. Storage and egress are excluded unless a platform note says otherwise.

Workload examplePlatform and monthly costEstimated difference

Small API

2 vCPU, 4GB RAM, 24/7

VercelEstimate

~$184/mo

Fly.ioEstimate

~$85/mo

Vercel 71% lower

Medium App

8 vCPU, 16GB RAM, 24/7

VercelEstimate

~$737/mo

Fly.ioEstimate

~$300/mo

Vercel 57% lower

Production Stack

16 vCPU, 32GB RAM, 24/7

VercelEstimate

~$1475/mo

Fly.ioEstimate

~$600/mo

Vercel 15% lower

Small API

2 vCPU, 4GB RAM, 24/7

VercelEstimate

~$184/mo

Fly.ioEstimate

~$85/mo

Vercel 71% lower

Medium App

8 vCPU, 16GB RAM, 24/7

VercelEstimate

~$737/mo

Fly.ioEstimate

~$300/mo

Vercel 57% lower

Production Stack

16 vCPU, 32GB RAM, 24/7

VercelEstimate

~$1475/mo

Fly.ioEstimate

~$600/mo

Vercel 15% lower

Vercel calculation: Active CPU @$0.128/hr (iad1) x vCPU-hrs; Provisioned Memory, bandwidth, Blob/KV/Postgres usage, and Pro seats ($20/user/mo) not included. Pricing varies by region.

Fly.io calculation: estimated using always-on VM pricing (CPU + RAM) across 720 hours/month

Sources:Vercel Pricing·Fly.io Pricing

Vercel Overview

Vercel is a frontend-first platform ("Frontend Cloud") optimized for frameworks like Next.js. It automates builds and deployments from Git, serves static assets on a global Edge Network, and runs backend logic through serverless and edge functions. Vercel excels at preview environments and fast front-end delivery, with usage-based pricing for compute, bandwidth, and storage add-ons (Postgres, KV, Blob).

Fly.io Overview

Fly.io is an edge application platform that runs apps as lightweight Firecracker micro-VMs across a global network. It emphasizes Dockerfile-first deployments and a powerful CLI (`flyctl`) for fast, scriptable workflows. Fly.io provides Anycast networking, global routing, per-region scaling, and scale-to-zero for idle workloads, making it a strong fit for latency-sensitive apps and globally distributed teams.