ChatGPT App vs Custom GPT: What Is the Difference? (April 2026)

When developers first look at building something inside ChatGPT, they usually find two options: Custom GPTs and ChatGPT Apps. The names sound related. They’re not, really. They’re built for different things, require different skills, and work in completely different ways.

TL;DR: Custom GPTs are no-code configuration. You write instructions, upload knowledge files, and optionally add API actions, and ChatGPT uses all of that to produce better text responses. ChatGPT Apps are coded applications built on the Model Context Protocol that render interactive UI directly inside the chat conversation. If your goal is a customized text assistant, use a Custom GPT. If your goal is a real interactive interface, you need a ChatGPT App.

What Custom GPTs Are

Custom GPTs let you configure a version of ChatGPT for a specific purpose without writing code. You give it a system prompt, optionally upload knowledge files (PDFs, docs, spreadsheets), and optionally wire up external API calls through the Actions feature. Someone chatting with your Custom GPT gets responses shaped by your configuration.

That’s the full scope. Custom GPTs can’t render UI. They can’t display a chart, show a form, or let users click a button. Every interaction is text in, text out. API actions can pull in real-time data, but the results come back as text that ChatGPT summarizes into a response.

Custom GPTs live in the GPT Store and only work inside ChatGPT. They’re a good fit for:

• Internal assistants tuned to a company’s documentation or style
• Customer-facing bots with domain-specific knowledge
• Lightweight task helpers where text responses are enough
• Prompt templates you want to reuse across conversations

What ChatGPT Apps Are

ChatGPT Apps are built with code. They run on the Model Context Protocol (MCP), which defines how interactive applications attach to AI conversations. When a ChatGPT App tool runs, the host loads your application inside a sandboxed iframe directly in the conversation. Users see a real interface, not a chat message describing an interface.

The iframe can contain anything you’d build as a web app: charts, forms, data tables, maps, multi-step wizards. The model stays connected throughout. When a user submits a form or clicks a button, the model sees that interaction and can respond. That back-and-forth between conversation and UI is what makes ChatGPT Apps different from everything else you can build on top of ChatGPT.

ChatGPT Apps are coded web applications. You write UI components (using any framework or vanilla JavaScript), define tools, and run an MCP server. There’s no configuration-only path. OpenAI provides an Apps SDK for building them, and open-source frameworks like sunpeak add testing, local development, and cross-host support on top.

Side by Side

	Custom GPT	ChatGPT App
Requires code?	No	Yes (web dev skills)
Output type	Text / markdown	Interactive UI (iframe)
API integrations	Via Actions (text responses)	Via MCP tools (full UI)
Works on ChatGPT	Yes	Yes
Works on Claude, VS Code, Goose	No	Yes
Where it lives	GPT Store	Any MCP host
Can combine with Actions?	Yes	No (mutual exclusion)
Typical use case	Domain-tuned assistant	Dashboards, forms, workflows

One limitation worth knowing: a single Custom GPT can use either Actions or Apps, but not both at the same time. If you want API Actions and an MCP App on the same GPT, you’ll need to pick one or restructure your approach.

The Cross-Host Difference

Custom GPTs are tied to ChatGPT. If you build one, it doesn’t work in Claude, VS Code, or Goose. There’s no equivalent concept on other hosts.

ChatGPT Apps are built on the MCP App standard, which is maintained under the Linux Foundation and supported by multiple AI clients. As of April 2026, ChatGPT, Claude (web and desktop), VS Code (via GitHub Copilot Chat), and Goose all render MCP Apps. An app you build today runs on every host that supports the standard, because the rendering model and communication protocol are the same everywhere.

This is worth thinking about early. If you build a Custom GPT, you’re scoped to ChatGPT’s user base. If you build a ChatGPT App using the MCP standard, your addressable users include everyone on every host that has adopted it. And more hosts are adding support.

Connecting to ChatGPT

To test a ChatGPT App in the real ChatGPT, you use Developer Mode. Developer Mode is available for ChatGPT Business, Enterprise, and Edu plans. Workspace admins enable it from Admin settings, and then you can point ChatGPT at your MCP server URL (local via tunnel or deployed) to test your app in the real environment.

For local development, you don’t need a ChatGPT account at all. A local inspector replicates the ChatGPT runtime so you can build and iterate without paying for a subscription or burning API credits.

Which One to Build

Build a Custom GPT if:

• You don’t want to write code
• Text responses are sufficient for your use case
• You’re building a knowledge assistant or domain-tuned chatbot
• You only need it to work in ChatGPT

Build a ChatGPT App if:

• You need interactive UI (forms, charts, dashboards, multi-step flows)
• You want your app to work across ChatGPT, Claude, and other hosts
• You’re building a product, not just a configured assistant
• You need programmatic logic beyond what prompt engineering can handle

The two aren’t mutually exclusive in concept, but remember they can’t coexist on the same GPT. If you’re starting from scratch and wondering which path to take, the decision usually comes down to one question: does your use case need a real interface, or is text enough?

Building a ChatGPT App

If you’ve decided ChatGPT Apps are the right fit, sunpeak is an open-source ChatGPT App framework that gives you everything you need to start. It includes a local inspector (so you can develop without a paid ChatGPT account), CLI scaffolding, 20+ typed React hooks, pre-built UI components, and a testing framework for unit, integration, and visual regression tests.

npx sunpeak new sunpeak-app
cd sunpeak-app
pnpm dev

Open localhost:3000 and you’ll see a ChatGPT inspector rendering your app. From there, connecting to the real ChatGPT is one tunnel command away.