Vercel vs. AWS

As AI technology advances, choosing the right platform is crucial for your team's speed, governance, and long-term success. Both Vercel and AWS 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 AWS 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. AWS at a Glance

Feature	Vercel	AWS
Infrastructure	Proprietary Edge/Serverless Platform	AWS-managed PaaS
Source Available
Deployment Options	Cloud only	AWS cloud only
Free Trial	Hobby free tier (4 Active CPU hrs + 360GB-hrs memory)	AWS free tier (limited)
Max vCPU per Service	Default 1 vCPU/function (Fluid Compute for more)	Plan-based (EC2 instance types)
Max RAM per Service	Default 2GB; higher via Fluid Compute	Plan-based (EC2 instance types)
Custom Domains	Hobby: 50/project; Pro: higher limits	(Route 53 / ALB)
Replicas per Service	Auto-scaled instances (no manual replica caps)	Plan-based (Auto Scaling)
Cron Jobs	Hobby: 2/day; Pro: 40/account (20/project)	CloudWatch/EventBridge
Log Retention	Short-term logs; up to 30d with Observability Plus	Configurable (CloudWatch)
Scale-to-Zero
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

AWSEstimate

~$90/mo

Vercel 72% lower

Medium App

8 vCPU, 16GB RAM, 24/7

VercelEstimate

~$737/mo

AWSEstimate

~$320/mo

Vercel 60% lower

Production Stack

16 vCPU, 32GB RAM, 24/7

VercelEstimate

~$1475/mo

AWSEstimate

~$600/mo

Vercel 15% lower

Small API

2 vCPU, 4GB RAM, 24/7

VercelEstimate

~$184/mo

AWSEstimate

~$90/mo

Vercel 72% lower

Medium App

8 vCPU, 16GB RAM, 24/7

VercelEstimate

~$737/mo

AWSEstimate

~$320/mo

Vercel 60% lower

Production Stack

16 vCPU, 32GB RAM, 24/7

VercelEstimate

~$1475/mo

AWSEstimate

~$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.

AWS calculation: EC2 + ELB + CloudWatch over 720 hours/month

Sources:Vercel Pricing·AWS Elastic Beanstalk 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).

AWS Overview

AWS Elastic Beanstalk is a mature AWS-native PaaS that automates deployment and scaling on top of EC2, ELB, Auto Scaling, and CloudWatch. It supports multiple runtimes, integrates deeply with AWS services, and lets teams deploy via the EB CLI or console. Beanstalk simplifies infrastructure management while keeping you inside the AWS ecosystem and cost model.