Top 6 AI App Builders: Lovable, Base44 & Glide
We tested the top 6 no-code/low-code AI app builders using 1 prompt across 15 dimensions, including setup, browsing, checkout, design, and usability.
AI app builder benchmark results
Read the benchmark methodology and evaluation to see how we tested these tools.
No-code & low-code app builders
No-code & low-code app builders feature comparison
Lovable
Lovable is best described as an AI-powered low- or no-code app builder with code-first output. Users primarily build through natural language prompts, iterative feedback, and browser-based editing rather than by writing code manually. However, unlike traditional no-code platforms, Lovable generates real React and TypeScript code, supports GitHub integration, and gives more technical users access to the underlying code and stack.
Lovable scored 18/20, the highest result in the benchmark. It generated a complete, working app with strong coverage of the main shopping, cart, checkout, admin, inventory, and persistence flows. Lovable’s main gaps were the lack of search/filter functionality and a cart item count indicator. We also found it the fastest and easiest tool to use, with the most visually polished output. The ability to export code or build apps natively added to its overall strength.
Base44
Base44 is an all-in-one AI app builder that turns plain-language descriptions into functional web apps and business apps. Wix acquired Base44 in 2025, providing the product access to Wix’s infrastructure, distribution, and website experience.
Base44 handles app structure, design, database, signups, user permissions, hosting, analytics, and integrations. Users can create complete apps without coding experience, connect APIs, use payment processors, and publish apps with a custom domain.
Base44 scored 16/20 and handled most core requirements well, including product browsing, stock indicators, search/filter, cart behavior, stock limits, reservation release, checkout pricing, admin updates, inventory changes, and session persistence. Its main weakness was usability: it was easy to use, but slower to respond than the strongest tools. One product image also failed to display in its main dashboard.
Softr
Softr is an AI-native no–code platform for business apps, customer portals, dashboards, and internal tools.
Softr offers drag-and-drop blocks, workflows, forms, user groups, responsive publishing, and integrations with tools such as Airtable, Google Sheets, Notion, HubSpot, monday.com, SQL databases, BigQuery, and REST APIs.
Softr’s AI Co-Builder creates the database, app, and business logic from a prompt, with security and permissions connected, which differentiates it from tools that generate UI or frontend code. It is well-suited for product teams and business users who want AI–built apps that connect to real data, support customers and users, and launch as operational software rather than prototypes.
Softr scored 12/20. Its search/filter feature, cart add/remove actions, cart expiration, checkout pricing, and admin workflows worked well. However, it missed several important commerce requirements, including stock indicators, stock-limit enforcement, cart item count, and state persistence. Softr also required several setup steps before testing, including design and layout choices, which provided greater control over presentation but slowed the evaluation flow.
Glide
Glide is a no–code app builder that turns spreadsheets and databases into mobile-first business apps. It is commonly used for internal tools, field apps, directories, CRMs, inventory trackers, and operational workflows, and connects to Google Sheets, Excel, Airtable, SQL sources, and Glide Tables
Users can create apps with a visual editor, templates, forms, roles, permissions, automations, and AI features that help summarize, classify, extract, and act on data.
Glide scored 11/20. It handled basic cart actions, showed cart count, released reserved stock, supported checkout pricing, and enabled admin updates. Its mobile and web views looked visually strong, and the agent was responsive and helpful. However, the publish/open flow did not work as expected; search/filter failed; stock limits were not enforced; and testing functions felt less direct than in other tools.
Bubble
Bubble is a full-stack no–code app builder for web and mobile app development. Bubble includes a drag-and-drop editor, built-in database, workflows, privacy rules, authentication, API integrations, marketplace resources, and AI-assisted app generation. Users can create custom apps, business apps, portals, dashboards, and native mobile apps for iOS and Android.
Bubble scored 10/20. It showed stock indicators and reflected checkout prices. However, it missed several central commerce flows: the cart did not update correctly, stock limits were not enforced, cart count was missing, search/filter failed, and admin order and inventory updates did not work as expected. Bubble’s editor was detailed, but the generated app needed more refinement and did not look as visually polished.
FlutterFlow
FlutterFlow is a visual low-code app builder for native mobile, web, and desktop apps.
FlutterFlow can export Flutter and Dart source code, allowing teams to extend the app beyond the platform when coding is required. FlutterFlow is a good fit for teams that want no-code speed at the start but still need generated code, code export, and developer control later.
It also supports AI agents for chat, image generation, video generation, speech-to-text, and text-to-speech inside apps.
In our benchmark, we excluded FlutterFlow from the final scored comparison. It offered a highly detailed design editor and may suit design-focused users, but it did not generate a complete, ready-to-test app from the prompt. Instead, it gave us a general structure and left most implementation work to us. Because the benchmark evaluated generated app outcomes, scoring FlutterFlow against the same criteria would not have been a fair comparison.
Code-first AI app builders
Ajouter comme source préféréeCode-first AI app builders feature comparison
Cursor by Anysphere
Cursor is an AI-native code editor rather than a classic no–code app builder. It allows product teams and developers to build apps, add new features, fix errors, and work across real codebases.
Cursor’s differentiation lies in its agentic coding environment and in-house Composer model, which is built for longer software engineering tasks, multi-step planning, and generating code changes across files. It is model-agnostic and provides access to models from OpenAI, Anthropic, Gemini, xAI, and Cursor, so teams can choose different models for different coding tasks.
Cursor supports AI autocomplete, chat with the codebase, code review, and terminal-aware development. It helps users create custom and AI-powered apps faster, but coding experience is still useful because users work directly with code.
Replit
Replit is a browser-based app development platform with a cloud IDE and AI agents. It can be used by hobbyists, students, founders, and enterprise teams to build apps and prototypes from plain-language prompts.
Replit Agent 4 can run multiple agents in parallel on the same project, use a visual design canvas, and produce multiple artifact types, including web apps, native mobile apps, slide decks, data apps, and animations.
It also supports payment processors such as Stripe for web apps and RevenueCat for mobile apps, and it includes workflows for building iOS and Android apps and submitting them for App Store review.
See the video below to learn how Replit’s Visual Editor works:
v0 by Vercel
v0 is Vercel’s generative UI and full-stack web app builder. It turns prompts into React, Next.js, Tailwind, and Shadcn UI interfaces and connects closely with Vercel’s deployment platform.
Users can import GitHub repositories, work on existing code, create commits, use branch and pull request workflows, and connect to Vercel project settings. It also supports data-connected apps via Snowflake and AWS database integrations, making it useful for internal tools and real-data applications.
Bolt by StackBlitz
Bolt is a browser-based AI-powered app builder for full-stack JavaScript app development.
With its StackBlitz WebContainers, which run a Node.js environment in the browser, Bolt speeds up the app creation process by allowing users to test real apps without installing dependencies locally.
Our experiences with AI app builders
Screenshot-to-code benchmark
Screenshot-to-code is a practical workflow for evaluating AI app builders, as many users start with a mockup, landing page, or app idea before moving to a working app. In our screenshot-to-code benchmark, we tested Lovable, v0, and Bolt on five design pages using the same prompt: “Create a pixel-perfect implementation of this UI design.”
We measured both quantitative element accuracy and qualitative UI fidelity. Quantitative scoring focused on whether boxes, buttons, text elements, images, icons, and input fields were correctly implemented. Qualitative scoring focused on typography, layout structure, visual elements, basic styling, and color usage.
In our benchmark, v0 and Bolt led the comparison. This suggests that teams using AI app builders should test design-to-code quality separately from other criteria such as generated code quality, GitHub integration, custom domain support, mobile app support, and the ability to create complete apps with real data. See the screenshot for the code for more details on the benchmark and output examples.
Note: We evaluated screenshot-to-code performance, not broader app development capabilities such as backend logic, built-in databases, integrations, API keys, code export, native mobile apps, payment processors, or app publishing. However, the benchmark is useful for comparing how Lovable, v0, and Bolt handle design-to-code tasks.
AI code editor benchmark
The AI code editor benchmark focused on a different question: can an AI coding agent build and validate a working web app with minimal human input? We tested six AI code editors across ten real-world web development challenges involving backend, frontend, authentication, and state management.
Evaluation combined backend correctness, frontend behavior, and overall performance. The setup used one-shot execution, followed by backend and frontend smoke tests. This allowed us to compare whether each agent produced a runnable system, met backend requirements, implemented expected frontend behavior, and handled the task reliably.
Cursor achieved the highest backend and combined score. The qualitative findings showed different engineering styles across the tools. Cursor favored small, low-risk fixes. Replit handled the workflow through its cloud environment. See the full comparison on AI code editor.
Note: These results should be treated as an autonomous coding and orchestration benchmark. We did not evaluate no-code editing, screenshot-to-code quality, built-in databases, mobile app publishing, custom domains, or broader business app workflows. However, the benchmark is useful for comparing how AI coding tools handle runnable systems, backend logic, frontend behavior, and full-stack development tasks.
AI app builders benchmark methodology
To evaluate AI app builders, we created free trial accounts for Lovable, Base44, Bubble, Glide, FlutterFlow, and Softr. Each tool was given the same prompt to generate an Inventory & Order System for an e-commerce use case with stock management, customer shopping flows, admin controls, order status updates, and overselling prevention.
The target app included two main user roles:
- Customer: Browse products, view available stock, manage a cart, check out, and view order history.
- Admin: Manage products and inventory, view orders, and update order status.
The core requirement was that the app should prevent overselling. Specifically, if a product has one item in stock and two users attempt to check out at the same time, exactly one checkout should succeed, while the other should receive an error. The expected data model included users, products, carts, cart items, orders, and order items, with support for temporary stock reservations and cart expiration.
We tested the generated apps in their test or preview environments. None of the apps were published publicly. Where possible, we opened the live preview or a test URL and evaluated the app as an end user would.
FlutterFlow was excluded from the final benchmark comparison. Unlike the other tools, FlutterFlow did not generate a complete working app from the prompt. Its design editor was highly detailed, but the output provided a general structure, leaving most of the implementation to the user. Because the other tools automatically generated more complete apps, including FlutterFlow in the same scoring framework, would not have been a fair comparison.
We evaluated each app using the following criteria:
- Setup: Whether the app opened successfully without errors and whether product data, images, and prices loaded correctly.
- Browsing: Whether customers could browse products, see stock levels, view correct stock indicators, and use search or filters.
- Cart: Whether users could add and remove items, see the cart count update, avoid adding more than available stock, and release reserved stock after cart expiration.
- Check out: Whether checkout reflected current prices and validated stock before completing the order.
- Admin: Whether admins could update order status and adjust product inventory, with changes persisting across the app.
- Data persistence: Whether cart contents, orders, and inventory changes remained after refresh or re-login.
- Usability: Whether the overall process was fast, easy to understand, and easy to complete.
- Design: Whether the app had a polished, coherent interface with clear layout, readable typography, consistent components, and a production-ready feel.
- We reviewed each app as a finished user interface, focusing on the quality of the visible user experience rather than the underlying code.
- We assessed whether the layout created a clear visual hierarchy, with important information and primary actions easy to identify.
- We evaluated whether UI components such as buttons, cards, inputs, and navigation elements used a consistent visual language throughout the app.
- We looked for well-handled product imagery, empty states, error states, loading states, and action confirmations.
- We considered the app’s overall cohesion, including whether it felt intentionally designed rather than an unmodified starter template.
The evaluation focused on observable app behavior and user-facing outcomes rather than the internal implementation. Each tool was judged on how completely and reliably it transformed the same prompt into a functional inventory and order management application.
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@misc{ermut2026,
author = {Ermut, Sıla},
title = {{Top 6 AI App Builders: Lovable, Base44 & Glide}},
year = {2026},
month = jul,
howpublished = {\url{https://aimultiple.com/ai-app-builders}},
note = {AIMultiple. Consulté le 3 Juillet 2026}
}
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