Best AI app builders (2026): What ChatGPT, Claude & Gemini Recommend

Lovable is the AI app builder the models name for this job. Ten AI models answered five buyer questions, and Lovable appeared in 50 of 50 answers and came first in 40 of 50. Bolt, Replit and v0 form the next tier: each is present in most answers and almost never first. An AI app builder turns a written description into a working app. This page counts which ones AI answers name. It does not test which one builds better software.

TL;DR

• Start with Lovable. Every model named it in every answer, and no other product came close on first place.
• Test Bolt, Replit or v0 as the alternative that suits your team. All three sit in most answers, and v0 never opened one.
• Below the top four, the answer depends on the model you ask. Base44 is a Google pick, Bubble a Perplexity pick and Cursor an Anthropic pick.
• Vendor-written guides feed these answers, but a heavily cited site does not buy a name. zite.com drew 63 citations and Zite was named in 8 answers.
• Give the same prompt to two or three builders on their free plans before paying for any of them.

1. Lovable

Pick Lovable if you are building a full-stack web app from a prompt without a developer and want the default every model reaches for first.

Measured: named 50 of 50 (Lovable 100%), first 40 of 50 (Lovable 80%), average position 1.32.

No model or model family held Lovable back in any answer. That makes it the only product on the page a buyer can pick without first asking which model is speaking. The recorded answers attach it to one reader in particular: the non-technical founder shipping a SaaS-style MVP. Superapp’s comparison describes the output as a React web app with a database and sign-in. The same page records GitHub sync, so the code can leave the builder. The limit is the format. The output is a web app, and a phone store app means wrapping it yourself. Its first-place count is high but not total. Bolt, Replit, Base44, Zite, Softr and Blink each opened at least one answer.

Pros

• Every one of the ten models named it in all five of its answers
• First place in 40 of 50 answers
• Builds a React web app with a database and sign-in
• GitHub sync lets the code move to a conventional workflow later

Cons

• A store app means wrapping the web app yourself
• Credits go on fixes as well as builds, per Superapp’s pricing notes

Pricing: credits weighted by task, with a free plan and a Pro plan.

Best for: non-technical founders building a SaaS-style web MVP.

2. Bolt

Pick Bolt if you want a fast in-browser prototype and a second option that nearly every model already lists beside Lovable.

Measured: named 48 of 50 (Bolt 96%), first 4 of 50 (Bolt 8%), average position 2.5.

Bolt is the most consistent runner-up on the page. Nine of the ten models named it every time they answered. The exception is Sonar Reasoning Pro, at 3 of 5. Its average position of 2.5 means that when an answer lists several builders, Bolt usually comes straight after Lovable. It also took four first places, the most of any product other than Lovable. Superapp’s comparison rates it the fastest text-to-prototype tool. That same page records token billing, and says token use grows with project size. For a buyer, that is the trade to weigh. A quick first draft is cheap, and a large project costs more per message.

Pros

• Present in 48 of 50 answers
• Four first places, more than any product except Lovable
• Can add a React Native version through Expo on request

Cons

• Token use grows with project size
• Sonar Reasoning Pro included it in only 3 of 5 answers

Pricing: billed in tokens, with a free plan and a Pro plan.

Best for: fast prototypes and landing pages, where Superapp’s prompt table places it.

3. Replit

Pick Replit if you want one agent to handle the backend, database and hosting, with room for a mobile app on the same backend later.

Measured: named 46 of 50 (Replit 92%), first 2 of 50 (Replit 4%), average position 3.67.

Replit is the product the models add when the answer turns to control and infrastructure. Every OpenAI answer included it. One went further. GPT-5.6 Sol made Replit Agent its default recommendation in one reply, saying “Replit currently offers one of the most complete all-in-one workflows”. Superapp’s comparison describes web apps and React Native mobile apps built on one backend. The same page warns that bills can spike. The counts carry one oddity. Replit appears in more answers than v0, yet its average position of 3.67 sits behind v0’s 3.47. The models name it often and tend to name it after the front-end tools.

Pros

• In 46 of 50 answers
• Included in every OpenAI answer (Replit 100% of the OpenAI family)
• Builds web and React Native apps on one backend
• Took two first places

Cons

• Bills can spike under effort-based billing, per Superapp’s ranking notes
• Average position 3.67, behind v0 despite more mentions

Pricing: effort-based billing, with a Core plan.

Best for: builders who want the backend and hosting in one place and a mobile app later.

4. v0

Pick v0 if your team already ships React and Next.js and wants generated UI code it can review as a pull request.

Measured: named 45 of 50 (v0 90%), first 0 of 50 (v0 0%), average position 3.47.

v0 has the widest gap on the page between being named and being named first. It appears in 45 answers and opens none. The models treat it as the specialist they mention, never the default they lead with. ChatGPT described it as “best for developers and teams already using React/Next.js/Vercel”. A likely reading of the gap follows from that framing. The prompts ask for a web app from a prompt, so the models open with a full-stack default and bring in a front-end tool after it. Superapp’s comparison describes Next.js, React, TypeScript, Tailwind and shadcn/ui output. It also records that v0 sends changes to GitHub as pull requests rather than pushing to main.

Pros

• Appears in 45 of 50 answers, and no model named it fewer than 3 times in 5
• Average position 3.47, ahead of Replit
• Sends changes as GitHub pull requests instead of pushing to main

Cons

• Zero first places across 50 answers
• Perplexity included it in only 3 of 5 answers
• Model costs add up, per Superapp’s ranking notes

Pricing: model-priced credits, with a free plan and a per-user paid plan.

Best for: React and Next.js teams that want production UI code.

5. Cursor

Pick Cursor if you can read code and want an AI editor rather than a hosted builder, which is the role the models give it.

Measured: named 21 of 50 (Cursor 42%), first 0 of 50 (Cursor 0%), average position 5.86.

Cursor opens the second tier, and the drop to it is steep. The top four each appear in 45 answers or more. Cursor appears in 21. The recorded answers name it as the developer’s route, not the founder’s. Sonar Reasoning Pro, for example, points technical readers to an AI-native editor such as Cursor or Replit for hands-on development. The Anthropic models named it most (Cursor 60% of Anthropic answers). ChatGPT did not name it once. Its average position of 5.86 puts it near the end of the answers that include it. No captured page records its pricing.

Pros

• Fifth on the page, with 21 of 50 answers
• Claude named it in 4 of 5 answers
• GPT-5.6 Luna, Claude Opus 5 and Gemini each named it in 3 of 5 answers

Cons

• ChatGPT left it out of all five answers
• Never placed first
• Pricing is not recorded in any captured page

Pricing: No public pricing is recorded.

Best for: developers who want hands-on control of the code.

6. Base44

Pick Base44 if you want the builder to host the web app for you and you are comfortable staying on one platform.

Measured: named 19 of 50 (Base44 38%), first 1 of 50 (Base44 2%), average position 4.26.

Base44’s count comes from a few models, not the whole panel. Gemini 3.5 Flash named it in every answer and Claude Fable 5 in 4 of 5. GPT-5.6 Sol, ChatGPT and Perplexity never named it. Its average position of 4.26 is better than Cursor’s despite fewer mentions, so the models that name it tend to list it early. Superapp’s comparison describes it as a builder of hosted web apps. According to that page, its mobile option runs the published app inside a web view. The same page records that code export is tied to Base44 infrastructure. A buyer who asks Gemini will likely hear about Base44. A buyer who asks ChatGPT will not.

Pros

• Gemini 3.5 Flash included it in all five answers
• Google models named it in 80% of their answers (Base44 80%)
• Average position 4.26, ahead of Cursor
• Took one first place

Cons

• Absent from every GPT-5.6 Sol, ChatGPT and Perplexity answer
• Mobile runs the web app inside a web view
• Export stays tied to Base44 infrastructure

Pricing: a free plan and a paid plan billed annually.

Best for: hosted web apps where the builder also runs the hosting.

7. Bubble

Pick Bubble if you need complex web app logic, such as a marketplace or a SaaS product, and accept finishing the AI draft in a visual editor.

Measured: named 16 of 50 (Bubble 32%), first 0 of 50 (Bubble 0%), average position 5.19.

Bubble is the Perplexity models’ pick. Perplexity and Sonar Reasoning Pro each named it in 4 of 5 answers. GPT-5.6 Sol, ChatGPT and Gemini 3.5 Flash never named it. The split matches how the captured guides describe it. ZEKAI’s guide ranks Bubble as a flexible platform for complex web apps. The same guide says its AI features feel less integrated than those of newer AI-native platforms. Superapp’s comparison lists it among the tools with no source code export. ZEKAI describes it as a long-standing no-code platform that has recently added AI features. Sonar Reasoning Pro groups it with the no-code business app tools, which fits that description.

Pros

• Perplexity and Sonar Reasoning Pro each named it in 4 of 5 answers
• Visual programming gives granular control over front end and back end logic
• Present in 16 of 50 answers

Cons

• Workload-based pricing can lead to bill shock as usage grows
• No source code export
• Mobile apps are web wrappers rather than native apps
• Not first in any answer

Pricing: workload-based, with a free plan for learning and development.

Best for: complex web apps such as SaaS products and marketplaces.

8. Zite

Consider Zite if you are building an internal tool, the job Perplexity names it for, and check it against the top four before you commit.

Measured: named 8 of 50 (Zite 16%), first 1 of 50 (Zite 2%), average position 5.88.

Zite shows the page’s clearest gap between being cited and being named. Its own site, zite.com, drew 63 citations in the recorded answers, third on the host list after youtube.com and lovable.dev. The models named Zite in 8 answers. Only Anthropic and Perplexity models named it. Claude Opus 5 flagged the source problem directly. Describing a guide that ranks Zite top, it added: “that’s Zite’s own blog”. Perplexity placed Zite among the stronger fits for internal tools. The section on citations below explains why this matters to a buyer.

Pros

• Led one answer
• Claude Opus 5 and Sonar Reasoning Pro each named it in 2 of 5 answers
• Perplexity grouped it with the internal-tool options

Cons

• No OpenAI or Google model named it
• Only 8 named answers against 63 citations to its own site

Pricing: No public pricing is recorded.

Best for: internal tools.

9. FlutterFlow

Pick FlutterFlow if the app has to reach phones as well as the web and you want Flutter code you can export.

Measured: named 7 of 50 (FlutterFlow 14%), first 0 of 50 (FlutterFlow 0%), average position 5.71.

FlutterFlow sits outside a web-first brief, and the counts reflect it. Six models named it, and none more than twice. When the models do name it, they file it under mobile. Claude separates the web-app generators from tools that produce publishable native or PWA apps, and puts FlutterFlow in the second group. Perplexity names it for native mobile apps. Superapp’s comparison says it generates pages and components into a Flutter project you can export. That page also records that the Flutter code export sits on paid plans. For a buyer who only needs a browser app, the models are signalling that this is the wrong shelf.

Pros

• Six of the ten models named it at least once
• Generates pages into an exportable Flutter project

Cons

• Missing from all OpenAI answers
• Code export requires a paid plan
• No model named it more than twice

Pricing: a free plan and a paid monthly plan.

Best for: apps that need to run on phones and in the browser.

10. Claude Code

Shortlist Claude Code only if you already work in code and put weight on GPT-5.6 Sol’s view, because that model accounts for the most mentions.

Measured: named 7 of 50 (Claude Code 14%), first 0 of 50 (Claude Code 0%), average position 6.43.

Claude Code is the page’s cross-family surprise. GPT-5.6 Sol, an OpenAI model, named it in 2 of 5 answers, more than any Anthropic model did. Claude Opus 5, Claude and Claude Fable 5 each named it once. ChatGPT, Gemini 3.5 Flash and both Perplexity models never did. Its average position of 6.43 is the second-latest on the page, so it tends to be the last name in a long answer. No captured page records its pricing or describes what it builds for this job. The counts say it is known to the models. They do not say the models consider it a prompt-to-web-app builder first.

Pros

• GPT-5.6 Sol named it in 2 of 5 answers
• Six models named it at least once

Cons

• Average position 6.43, near the end of the answers that include it
• Absent from both Perplexity models
• No public pricing is recorded

Pricing: No public pricing is recorded.

11. Softr

Pick Softr if you want a secure web app or client portal built on data you already keep in a spreadsheet or database, which is where the captured guide places it.

Measured: named 6 of 50 (Softr 12%), first 1 of 50 (Softr 2%), average position 6.

Softr is the plainest case of a search result and the AI answers disagreeing. ZEKAI’s guide names it the best AI app builder for most users. The panel named it in 6 of 50 answers. Four models named it at all: Claude and Sonar Reasoning Pro twice each, Claude Opus 5 and Perplexity once each. It did open one answer. ZEKAI describes it building apps on top of Google Sheets, Airtable, HubSpot, BigQuery or a SQL database. The same guide says it is web-first and does not publish native apps to the Apple App Store or Google Play. For a data-first internal tool, it is worth a test. For a consumer web app from a blank prompt, the models rarely reach for it.

Pros

• Builds apps on top of existing data sources
• Opened one answer
• Offers a free tier

Cons

• Does not publish native mobile apps to the app stores
• Only four models named it

Pricing: a free tier and paid plans.

Best for: portals and internal tools built on existing data.

12. Emergent

Shortlist Emergent only if Anthropic’s models are the ones you are checking against, because they account for most of its mentions.

Measured: named 6 of 50 (Emergent 12%), first 0 of 50 (Emergent 0%), average position 5.83.

Emergent is an Anthropic-side name. Claude Opus 5 named it in 3 of 5 answers, Claude in 2 and Sonar Reasoning Pro in 1. No OpenAI or Google model named it at all. Its own site, emergent.sh, drew 13 citations in the recorded answers, the third-largest vendor-owned host after lovable.dev and zite.com. The same pattern as Zite shows here at a smaller scale: the vendor’s pages were retrieved, and the name reached 6 answers. No captured page records its pricing or its product scope. A buyer should treat it as a model-dependent mention, not a panel-wide recommendation.

Pros

• Claude Opus 5 named it in 3 of 5 answers (Emergent 60%)
• Three models named it

Cons

• Zero mentions from OpenAI or Google models
• First in none of its six answers

Pricing: No public pricing is recorded.

13. Windsurf

Shortlist Windsurf only if Gemini is the model you trust on this question, because Gemini supplied most of its mentions.

Measured: named 4 of 50 (Windsurf 8%), first 0 of 50 (Windsurf 0%), average position 6.25.

Windsurf rests on one model. Gemini named it in 3 of 5 answers (Windsurf 60%). Claude named it once. The other eight models never named it. Its average position of 6.25 puts it late in the answers that include it. No captured page covers Windsurf, so this page has nothing to say about its pricing or scope. What the counts do say is narrow and useful. A buyer asking Gemini may see Windsurf on the list. A buyer asking any other model is unlikely to.

Pros

• Gemini named it in 3 of 5 answers
• Appears in answers from two model families

Cons

• Eight of the ten models never named it
• No first places
• Pricing absent from every captured page

Pricing: No public pricing is recorded.

14. Blink

Consider Blink if you want a builder that wires billing into a SaaS MVP from the start, which is how the Perplexity models describe it.

Measured: named 2 of 50 (Blink 4%), first 1 of 50 (Blink 2%), average position 1.5.

Blink has two mentions and still the second-best average position on the page, 1.5. Both came from the Perplexity family, one each from Perplexity and Sonar Reasoning Pro, and both in answers to the SaaS MVP question. Sonar Reasoning Pro put it first. Perplexity called it “the most aggressive “vibe code to live product” option” because it ships database, auth, storage, billing and deployment natively. When the Perplexity family names Blink, it names it early. No other model family named it once. The counts support a narrow reading: Blink is a strong answer for one model family on one kind of question.

Pros

• Average position 1.5 when named
• Opened one answer, from Sonar Reasoning Pro

Cons

• Two mentions in 50 answers
• Only the Perplexity family named it

Pricing: No public pricing is recorded.

Best for: SaaS MVPs that need billing wired in from the start.

15. Firebase Studio

Leave Firebase Studio off this shortlist unless GPT-5.6 Luna’s answers match your situation, because it is the only model that named it.

Measured: named 2 of 50 (Firebase Studio 4%), first 0 of 50 (Firebase Studio 0%), average position 6.5.

Firebase Studio has the narrowest footprint on the list. GPT-5.6 Luna named it in 2 of 5 answers. No other model named it, including the two Google models and the other two OpenAI models. Its average position of 6.5 is the latest on the page, so even GPT-5.6 Luna mentions it at the end of a long answer. It never came first. No captured page describes its pricing or what it builds for this job. For a buyer, the counts put Firebase Studio outside the shortlist on this question.

Pros

• GPT-5.6 Luna named it in 2 of its 5 answers (Firebase Studio 40%)
• Among the 15 products named at all, while Rocket and Create were never named

Cons

• Nine of the ten models never named it
• Latest average position on the page, at 6.5

Pricing: No public pricing is recorded.

How do the tools compare?

Answer share is the share of the 50 recorded answers that named a product. Named first is the share of answers where it appeared before any other tracked product. The full record, with every answer, is on the AI app builders index.

The pricing models for Lovable, Bolt, Replit, v0, Base44 and FlutterFlow come from Superapp’s comparison. The pricing models for Bubble and Softr come from ZEKAI’s guide.

Lovable leads on every measure. Below it the pattern is a cliff, not a slope. Four products appear in 45 answers or more. The fifth, Cursor, appears in 21. Everything after Cursor is named by a minority of the answers. The first-place column is starker still. Lovable holds 40 of the 50 first places, and v0, present in 45 answers, holds none. Seventeen products were tracked and 15 were named. Rocket and Create were never named, so they carry no row.

Where do the models disagree?

The models agree completely on the leader. All ten named Lovable in all five of their answers, and all four model families led with it. The disagreement is in the tail, and it is large.

ChatGPT gives the narrowest answers. Across its five replies it named Lovable, Bolt, Replit and v0 every time and no other tracked product once. A buyer who only asks ChatGPT sees a four-product market.

Gemini 3.5 Flash is the Base44 model. It named Base44 in every answer, while GPT-5.6 Sol, ChatGPT and Perplexity never did.

The Perplexity pair reach for no-code platforms. Perplexity and Sonar Reasoning Pro named Bubble in 4 of 5 answers each, and they are the only models to name Blink. Sonar Reasoning Pro is also the one model that left Bolt out, naming it in 3 of 5.

The Anthropic models carry the developer tools. Claude named Cursor in 4 of 5 answers, and Claude Opus 5 named Emergent in 3 of 5. Neither product appears in a ChatGPT answer.

Two products depend on a single model. Windsurf’s mentions come mostly from Gemini, and Firebase Studio’s come only from GPT-5.6 Luna.

Why does a heavily cited vendor site not buy a place in the answer?

Because a citation shows that a model read a page, and a name shows that the answer agreed with it. The counts separate the two, and no single table on this page shows both at once.

The recorded answers lean on vendor-written material. The top cited hosts were youtube.com (171), lovable.dev (69), zite.com (63), catdoes.com (40), vibecodingacademy.ai (38), daily.dev (30), banani.co (27) and superappp.com (23). The vendor-owned hosts among all citations were lovable.dev (69), zite.com (63), emergent.sh (13), replit.com (11) and docs.lovable.dev (9). Claude Opus 5 noticed this while answering, and opened one reply with a warning: “nearly every source below is published by a company that sells one of these tools, and each one happens to rank its own product first.”

The captured search results show the same thing from the other side. The Superapp guide among them ranks Superapp first, under a disclosure that Superapp is its own product. ZEKAI’s guide lists sources that include roundups published by Zite, Softr, Adalo and Base44.

The finding is that retrieval did not become recommendation. Lovable’s own sites drew 69 and 9 citations, and Lovable was named in all 50 answers. Zite’s site drew 63 citations, close to Lovable’s main site, and Zite was named in 8. Emergent’s site drew 13, and Emergent was named in 6. A vendor can get its own page read by the models. The counts show that this alone did not put the vendor’s name into most answers. One plausible mechanism is that the models weigh a claim by how many independent pages repeat it. The counts are consistent with that, and they do not prove it.

For a buyer, this is the reason to trust the four names every model agrees on more than the tail. The tail names depend on which model is asked and which vendor pages it happened to retrieve. Citation counts reflect only the citations returned in the recorded API responses, and coverage varies by model.

How was the sample built?

10 models x 5 fixed prompts = 50 recorded answers. Each model answered each prompt once, in the 2026-09 edition. The five questions, verbatim:

1. What is the best AI app builder for building a web app from a prompt? Name specific products.
2. Which AI app builder would you recommend to building a web app from a prompt in 2026?
3. Compare the top AI app builder options right now.
4. I’m building a web app from a prompt and I need an AI app builder. What should I use and why?
5. Best AI app builder for building a web app from a prompt to vibe code a SaaS MVP?

The ten models come from four families. OpenAI contributed GPT-5.6 Sol, ChatGPT and GPT-5.6 Luna, for 15 answers. Anthropic contributed Claude Opus 5, Claude and Claude Fable 5, for 15 answers. Google contributed Gemini and Gemini 3.5 Flash, for 10 answers. Perplexity contributed Perplexity and Sonar Reasoning Pro, for 10 answers. The panel tracked 17 products and 15 were named. The full method is on the method page.

How does this sit against the AI app builder guides?

The pages ranking for this query rank products for purchase. This page counts the names AI answers produce. They answer different questions, and they reach different lists.

Superapp’s guide is a long ranked list of text-to-app generators, with prices, billing units and example prompts. It puts Superapp first and discloses that Superapp is its own product. For a web app, it names Lovable, Bolt and v0 as the leading text-to-app tools. That web shortlist overlaps closely with the top of the answer counts here.

ZEKAI’s guide is a four-product shortlist. It names Softr the best AI app builder for most users, followed by Adalo, Bubble and Amabrik. It describes its reviews as independent and not influenced by any vendor. Lovable, Bolt, Replit and v0 are not on its list. The panel named Softr in 6 of 50 answers, so this guide and the AI answers point a buyer in different directions.

The other fetched result is a YouTube video in which one creator builds a single app with Puter AI Builder. The video is sponsored by Puter. Puter is not among the products this panel tracks.

This page adds three things none of them carry: first-place counts, the model-by-model split and the citation hosts behind the answers.

What can these counts not tell you?

They cannot tell you which product is better. The counts measure presence in recorded answers, not quality, reliability, support or fit with your stack. Being named also differs from being recommended, because an answer can list a product in order to warn against it. Each model answered each prompt once, so a single answer can move a vendor’s count. The data is one dated snapshot from the 2026-09 edition. Product names are matched as text against known aliases. Answers came through model APIs and can differ from what the consumer chat apps show. All five prompts were in English. No position on this page is sold, sponsored or influenced by any vendor.

What should a buyer do with this?

Shortlist Lovable and one of Bolt, Replit or v0, chosen by your team. Pick Bolt for quick prototypes, Replit if the backend and a later mobile app matter, and v0 if your team already works in React and Next.js. Then run the same prompt through each on a free plan. Superapp’s guide gives the same advice: most of these builders offer free tiers, so the easiest test is to give each the same prompt. Check how each one bills before a long build. Credits, tokens and effort-based billing each charge for fixes, and the fixing is where credits go. Treat any name below the top four as a model-dependent suggestion. If a product only appears when you ask one model, check it against the others before you commit.

Frequently asked questions

What is the best AI for building web apps?

By AI answer count, Lovable. Ten AI models answered five buyer questions about building a web app from a prompt, and every model named Lovable in every answer. It came first in 40 of 50 answers. Bolt, Replit and v0 were each named in 45 answers or more. These counts measure which product the models name, not which one builds better software.

Is there a free AI app builder that uses a prompt to create apps?

Yes, several offer free plans. Superapp’s comparison lists free plans for Lovable, Bolt, v0, Bubble, FlutterFlow and Base44, and describes them as plans for testing. ZEKAI’s guide records a free tier for Softr. The panel does not measure price.

Can ChatGPT create web apps?

The panel did not test whether ChatGPT builds web apps itself, and none of the captured pages test it. What it recorded is where ChatGPT sends people. In all five of its answers, ChatGPT named Lovable, Bolt, Replit and v0, and it named no other tracked builder. ZEKAI’s guide suggests starting by describing the app to a large language model to refine the features before building.

How do you build a web app with AI?

Describe the app to an AI app builder, then refine it message by message. Superapp’s guide suggests saying who uses the app and what they do most, listing the screens and naming the data. It also advises saying whether the app should run on the web or a phone, asking for a plan first and building one screen at a time. Most builders assume a web app unless told otherwise.

Why is v0 never named first?

The models name v0 in 45 of 50 answers and put it first in none. The recorded answers frame it as a front-end tool for teams already on React and Next.js. The prompts ask for a whole web app, so the models open with a full-stack builder and add v0 after it. That is a reading of the answers, not a measured cause.

Does a high answer count mean the product is better?

No. Answer share counts presence in recorded answers. It says nothing about uptime, support, pricing fairness or fit with a particular stack. Use it to decide which products to test, then test them on your own prompt.

Which AI app builder can build a mobile app as well as a web app?

Superapp’s comparison describes Replit building web apps and React Native mobile apps on one backend. It describes FlutterFlow generating an exportable Flutter project. It records that Bolt can add a React Native version through Expo. Lovable, v0 and Base44 produce web apps.