Side-by-side

Continue vs Lovable

ContinueLovable

Bottom line: Continue for software development teams wanting configurable AI tooling; Lovable for founders and solo builders shipping MVPs fast.

	Continue Continue is an open-source AI coding assistant that brings autocomplete, in-IDE chat, and agentic edits to VS Code and JetBrains, with support for any model. Visit	Lovable Lovable is an AI-powered app and website builder that generates working prototypes from natural language descriptions or screenshots Visit
Votes	0	0
Pricing	Freemium	Freemium
Category	Coding	Coding
Tags	write-code	write-codebuild-appsbuild-websites
Best for	Software development teams wanting configurable AI tooling Developers who value open-source transparency Engineering organizations standardizing workflows with custom agents	Founders and solo builders shipping MVPs fast Non-technical makers who want functional apps without coding Product and design teams prototyping ideas
Pros	Open-source foundation gives teams full transparency into how the assistant behaves and the freedom to adapt it to their own workflows. Works across major editors including VS Code and JetBrains, fitting into existing developer environments rather than forcing a tool switch. Custom AI agents can be source-controlled and shared, letting teams encode their own standards and reuse consistent automation across projects. Flexible model access through a credit system means teams can choose frontier models that match their needs instead of being locked to one provider. Integrations with Slack, Sentry, and Snyk extend AI assistance beyond the editor into the wider development and incident workflow.	Generates working, deployable web apps from plain-language prompts, screenshots, or docs, dramatically lowering the barrier to building a functional prototype without writing code. Real-time preview and conversational iteration make it fast to refine results, with one-click deployment to lovable.app subdomains or custom domains. Native Supabase integration handles database and authentication needs, so generated apps can move beyond static front-ends to real, data-backed products. Strong collaboration and governance options, including unlimited collaborators, user roles, SSO, SCIM, and audit logs, make it viable for teams and larger organizations. A genuinely usable free tier with daily build credits plus a template library lets new users validate the workflow before committing to a paid plan.
Cons	The recent acquisition by Cursor creates uncertainty around the product's future direction, subscription continuity, and long-term roadmap. A credit-based model billing structure can make spend less predictable than a flat subscription, especially for teams using premium frontier models heavily. Building and tuning custom agents requires upfront configuration effort and a degree of technical comfort that casual users may find demanding. Post-acquisition, the long-term status of standalone hosting and the open-source project may shift, introducing potential lock-in or migration concerns.	The credit-based pricing model makes spend hard to predict, since each message consumes credits by complexity and iterative fixes can quietly burn through your balance. Generated code can require manual correction, and the AI sometimes introduces issues while attempting to fix others, which adds cost and frustration on complex builds. It is web-focused, so teams needing native mobile apps, heavy backend systems, or deep custom infrastructure will hit limits. Reliance on the platform and its Supabase-centric stack introduces a degree of lock-in that should factor into long-term planning.

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