Base44 vs Lovable

Both products can turn a sentence into a deployed web app. If you are comparing base44 vs lovable, the pricing pages alone will not settle it because the numbers look similar and the meters measure different things. One useful way to compare them is to ask what code, data, and infrastructure you control after the app is deployed.

The usual version of this comparison says Base44 bundles its own backend while Lovable connects Supabase, so Lovable is the portable one. That was true and it is now out of date. Since Lovable Cloud shipped, new Lovable projects get a built-in backend by default: still Supabase's open-source stack underneath, but an instance Lovable owns. It does not appear in your Supabase dashboard, you get no database URL and no service role key, and Lovable's own docs say there is no migration from Cloud to a Supabase project you own.

You can still connect your own Supabase project instead, and that option is fully supported. It is a choice you have to make deliberately, at the start, before you have data. Make it later and the docs tell you to recreate the schema and move the rows by hand.

The two products are therefore closer than older comparisons may suggest. Backend choice, data access, and migration options deserve as much attention as the plan price.

What both get right

Both products can produce a first version quickly. You describe the app, and a few minutes later there can be a URL with a login screen and a database behind it, without manually configuring a connection string or hosting region. That can be useful for validating an idea, showing a stakeholder something clickable, or building a small internal tool.

Both also handle setup tasks that can slow down a new project, including deployment, HTTPS, database provisioning, and file uploads.

Where they actually differ

Base44

Lovable

Database

Bundled. Nothing to connect, nothing to choose.

Lovable Cloud by default: Supabase's stack, on an instance Lovable owns. Bring your own Supabase project instead if you choose it up front.

Your own Postgres, reached through Prisma and Kysely.

Time to first version

Minutes, from a sentence.

Minutes, from a sentence.

Manual setup: run the CLI, provision Postgres, configure the environment, then start editing code.

Cost while building

Message credits, spent per instruction.

Build credits, spent per instruction.

One payment per pack, plus hosting and third-party services.

Cost once live

Integration credits, spent by your users' actions.

Cloud and AI usage, billed on top of the plan.

Your hosting bill, whatever you negotiated it to be.

Leaving

GitHub export from the Builder plan, but the app assumes their platform.

Depends entirely on which backend you picked on day one. Your own Supabase project is portable. Cloud has no supported migration out.

No template platform to leave. The code was in your repository from the start.

See what a template includes

If you expect to stay on the platform, Base44's bundling is a feature: fewer moving parts, one bill, one support channel. If you suspect you will eventually want out, Lovable can still give you that, but only if you connect your own Supabase project when you create the app. That early choice materially affects the later migration path.

The credit model, and when it stops being cheap

On both platforms, credits are charged for instructions rather than successful results. If an instruction needs correction, the follow-up instruction uses more credits.

That model can be economical while the app is small and instructions produce useful results. Costs become less predictable when a bug is difficult to describe or the relevant code is unfamiliar, because each revision is metered.

Then there is the second meter. Base44 charges integration credits for actions your live app performs, and its docs are clear that unused monthly credits expire rather than rolling over. Lovable meters Cloud and AI usage, covered first by a grant of 20 Cloud and 4 AI credits a month that its own documentation calls temporary and subject to change, and then by your general credits. Once the grant runs out, user activity can draw from the same general credit pool used for building.

Treat every number below as a snapshot rather than a quote. Both companies have repriced more than once, and the structure is the part worth comparing anyway: two meters, one that stops when you stop building and one that does not.

The part that is hard to undo

Credits are visible on the invoice. Platform dependence is less visible and may matter more if you later need to move the application.

Moving hosting or frameworks can be possible when the application uses documented, accessible infrastructure. Leaving a platform is harder when it controls the runtime, database, auth, and deployment pipeline together, because migration then involves several coupled parts.

That coupling may be acceptable for a prototype or an app expected to remain on the platform. For a business-critical system, price changes, plan changes, missing capabilities, and provider incidents become operational dependencies. If the exported application cannot run independently, leaving may require a partial or full rewrite.

Where Hype Stack lands

Hype Stack takes a different approach: a slower initial setup in exchange for direct control of the repository and infrastructure.

The third option is below with its pack list and running screens. It requires more setup, but the application code and infrastructure choices remain under your control.