Vercel vs AWS
Both host production apps well. The question is not which company is bigger. It is whether your workload fits inside a function that has to finish fast.
The short answer
Choose Vercel when you are shipping a Next.js product and have no platform team; choose AWS when your compute shape or your scale economics have outgrown a managed function host.
Company size is a poor predictor here. We have watched a five-person team need AWS in month three because a background job ran long. We have also watched a funded product stay on Vercel for years, because its work is genuinely request-shaped.
The real question is what your code does. Does it answer a request in under a minute? Or does it hold a connection, run a queue, or process a job that takes longer than that?
Side by side
From each platform's own documentation, checked August 2026.
| Dimension | Vercel | AWS |
|---|---|---|
| What you manage | Git push triggers a build and deploy | You choose and wire the services yourself |
| Function duration | 300s default and max on Hobby; 300s default, 800s max on Pro and Enterprise | Lambda allows up to 900 seconds (15 minutes) per invocation |
| Request or response size | 4.5 MB documented ceiling, returns 413 beyond it | Payload limits vary by service; EC2 and containers have none of Vercel's shape |
| Long-running processes | Not supported; work must fit a function invocation | Native, on EC2, ECS or Fargate |
| Networking into a private VPC | Not a first-class feature | Native VPC peering, security groups, private subnets |
| Region control | Functions run in a single region by default | You pick the region per service, and can span several |
| Egress-heavy workloads | Billed per project, harder to forecast at volume | Priced per service, more levers to control it |
| Operational load | Near zero; the platform owns the pipeline | Real; someone owns the account, the VPC, the IAM policy |
- RequestA user asks a question.
- Model callOften the fast part.
- Retrieval or tool useMultiple round trips add up.
- Function ceiling300s or 800s, then a 504.
- Queue, elsewhereThe job that actually finishes.
An agent that chains tool calls or a document pipeline that embeds a large file rarely finishes inside a serverless function. That is a queue on infrastructure you control, not a longer timeout setting.
Vercel
Where it wins
- Preview URLs on every pull request, which turns review into clicking the real thing.
- Zero-maintenance deploy pipeline. Nobody owns build servers or release scripts.
- Next.js features arrive supported first, since the same company builds both.
- Instant rollback, because previous deployments stay addressable.
Where it hurts
- Function duration is capped: 300 seconds on Hobby, up to 800 seconds on Pro and Enterprise, both documented.
- The 4.5 MB request and response ceiling breaks upload flows built for a normal server.
- No native VPC, so reaching a private database or internal service takes extra work.
- Usage-based pricing is hard to forecast before real traffic arrives.
AWS
Where it wins
- Lambda documents up to 900 seconds per invocation, and EC2 or containers have no invocation limit at all.
- Native VPC networking, so a private database or internal API is a normal connection, not a workaround.
- You choose the region per service and can run in several at once.
- Every layer, compute, network, storage, is priced and tuned on its own, which matters once volume is real.
Where it hurts
- Nobody deploys it for you. Someone on the team owns the account, the IAM policy and the pipeline.
- No preview URL per pull request out of the box; you build that yourself or add a tool for it.
- More services means more surface to misconfigure, and a bad security group is a real incident.
- Small projects pay in setup time what they save in ceiling headroom they will never hit.
How to choose
- Choose Vercel if the product is Next.js, the team has no platform staff, and every job answers a request in well under a minute.
- Choose AWS if a job routinely runs past 300 seconds, holds a queue, or needs a private network into a database or internal service.
- Choose AWS if egress or compute at your traffic level is the largest line in the hosting bill and you need to tune it directly.
- Choose both if the front end is genuinely request-shaped and the heavy work is not. Vercel serves the app; AWS runs the queue behind an API.
- Choose neither yet if you have no production traffic. Model the actual shape of the workload before picking infrastructure for it.
AI systems that outgrew a request-response shape
Questions teams ask before moving
01Does Vercel get more expensive than AWS at scale?
Often, yes, once traffic and compute grow. Vercel bills per project on a usage model, with fewer levers to tune than AWS gives you per service. The crossover point depends on your actual traffic and job shape, not a fixed size of company. Model your own numbers before assuming either direction.
02Can we run part of our app on Vercel and part on AWS?
Yes, and it is the common pattern for AI products. The Next.js front end and any request-shaped API stay on Vercel. Long jobs, queues and anything needing a private network move to AWS, and the two talk over an API.
03What is the actual signal that we should move off Vercel?
A function timing out. Vercel documents this as a 504 with FUNCTION_INVOCATION_TIMEOUT once a job runs past its plan's duration cap. The first time you see that error in production is the signal, not a general sense that the app has grown.
04How hard is it to move from Vercel to AWS later?
The Next.js application itself is portable and can be self-hosted or containerized. What does not move so easily is the deploy experience. Preview URLs, instant rollback and zero-maintenance builds are habits your team will have to replace with tooling of your own.
