Greta.sh vs ChatGPT Canvas: Conversational Coding vs Vibe Building

TL;DR: Greta.sh and ChatGPT Canvas are in different categories despite both being 'use AI to write code.' Canvas is a collaborative writing and code editing interface within ChatGPT: highlight a section, ask the model to change it, see the edit in place. On May 28, 2026, OpenAI removed canvas from GPT-5.5 Instant and GPT-5.5 Thinking (coding now happens in code blocks in chat), and paid users keep canvas on legacy models only until those models are sunset. Greta.sh is an AI app builder that exports clean, portable Next.js code and deploys in one click, with a database and GitHub version control on the Pro plan. Canvas (or chat code blocks) suits working on existing code, prototyping snippets, learning, refactoring isolated code, and code review. Greta.sh suits building web apps, internal team tools, and customer-facing sites you'll deploy. The workflow can combine both.

Introduction

ChatGPT Canvas launched in October 2024 as OpenAI's interface for writing and coding projects: it opens in a separate window next to the conversation, and the model and user edit the same document or code. The interaction feels like collaboration: highlight a section, ask the model to refactor; the model edits in place; you continue working. In December 2024 OpenAI made it available to Free and paid users and added Python code execution. On May 28, 2026, OpenAI announced that canvas is no longer available in GPT-5.5 Instant or GPT-5.5 Thinking: writing and coding now happen directly in chat through writing blocks and code blocks, and paid users can keep using canvas through legacy models until those models are sunset.

Greta.sh is an AI-native app builder. Prompt-driven creation exports clean, portable Next.js code, deploys in one click with SSL and a global CDN, and on the Pro plan adds a database and version control with GitHub; projects can also connect Supabase. Output is a real codebase, not a panel artifact.

The 'Greta.sh vs ChatGPT Canvas' comparison gets asked because both involve AI helping with code. They're in genuinely different categories. Canvas is a collaborative editing environment within a chat product. Greta.sh is an app builder producing deployable applications. Conflating them produces frustration: Canvas users wondering why there's no deployment story; Greta.sh users wondering why anyone uses Canvas when full apps are buildable. (If you want OpenAI's own option for building and publishing a site, that is now ChatGPT Sites, a separate feature covered below.) This guide explains what each does and the realistic decision.

The category difference

ChatGPT Canvas is a collaborative coding/writing interface within ChatGPT. Code appears in a side panel; the model and user can both edit; you can restore previous versions. Coding shortcuts include review code, add logs, add comments, fix bugs, and port to another language, and canvas can run Python and render React/HTML previews that you can share with another user. Hosting a published site or app is not what canvas does; in ChatGPT, that is the job of ChatGPT Sites. Canvas is a sophisticated surface for working on code together with the model.

Greta.sh is an AI app builder. Users describe what they want; Greta.sh builds the app, exports clean Next.js code, and deploys it in one click with SSL and a global CDN (paid plans). The Pro plan adds a database, version control with GitHub, and team management.

Canvas is the collaborative editor layer; Greta.sh is the production build layer. Different jobs entirely.

Side-by-side comparison

What ChatGPT Canvas does well

• Collaborative code editing --- highlight + ask for change; model edits in place
• Working on existing code --- paste in; iterate together
• Learning by example --- generate code; understand by reading
• Single-file utilities and scripts
• Quick refactoring tasks
• Code review with model providing suggestions
• Writing tasks (Canvas also handles prose)
• Pair-programming feel with the model

What ChatGPT Canvas doesn't do

• Host or publish a site or app (in ChatGPT, that is ChatGPT Sites)
• Run in GPT-5.5 Instant or GPT-5.5 Thinking (removed May 28, 2026)
• Provide a database for an app (ChatGPT Sites has built-in storage)
• Replace a full development environment for complex projects

What Greta.sh does that Canvas doesn't

• Generate complete web apps and websites from prompts
• Export clean, portable Next.js code
• One-click deployment with SSL and a global CDN, plus custom domain setup (paid plans)
• Database and version control with GitHub (Pro plan), plus Supabase integration
• Connectors for OpenAI, Claude, Gemini, xAI, Slack, Resend, AWS SES, GitHub, and Netlify
• Team projects with one Owner plus Editors and Viewers (team management on Pro)
• Web analytics (Starter and up) and self-growing websites that keep improving SEO and AI-search readability after launch, guided by analytics
• A marketplace with 100+ templates to start from

When Canvas wins

On GPT-5.5 Instant and GPT-5.5 Thinking, the same snippet-level work now happens in code blocks directly in chat; canvas itself remains only on legacy models for paid users until those are sunset.

• Working on code you already have
• Quick prototyping of a snippet or function
• Learning by collaborating with model on existing code
• Refactoring tasks on isolated code
• Single-file scripts and utilities
• Code review and suggestion mode
• Writing prose alongside code (mixed projects)
• When you're already in ChatGPT for other work

When Greta.sh wins

• Building web products for customers
• Internal tools your team will use daily
• Customer-facing apps that need a database
• Any app you'll deploy to real users
• Applications you'll evolve over months and years
• Apps integrating with external services
• Sites you want to keep improving for SEO and AI search after launch

The realistic workflow combining both

You can use both for different jobs. Canvas (or code blocks in chat) for thinking through code, prototyping snippets, working on isolated pieces. Greta.sh for building and deploying the app. Cursor or a similar AI IDE for ongoing maintenance on the exported code.

Example workflow

• Use Canvas to prototype a specific algorithm or component approach
• Use Canvas to think through an architectural question with the model
• Use Greta.sh to build and deploy the actual app
• Use Cursor or similar AI IDE for ongoing feature work and maintenance
• Each tool plays to its strengths

Canvas vs Artifacts vs Greta.sh — quick clarification

All of these involve AI generating code, but they're different tools:

Artifacts and Canvas serve similar 'work with code in chat' jobs with different interaction models. Greta.sh is in a different category: building deployable applications with exportable code, not panels in chat. ChatGPT Sites is OpenAI's hosted option; per OpenAI it is in public beta on eligible Plus, Pro, Business, Enterprise, and Edu plans, and it offers built-in storage, optional Sign in with ChatGPT, and custom domains.

Common project patterns

Working on a single algorithm

Canvas wins. Iterate on the algorithm with model. Refactor together. Once you're happy, copy to your project.

Building a real SaaS

Greta.sh wins. A database (Pro plan), one-click deployment, and exportable Next.js code are part of the product; canvas edits code but doesn't host an app.

Learning a new framework

Canvas wins. Generate examples; modify together with model; understand by doing.

Refactoring existing code

Canvas wins for isolated refactoring; Cursor or similar AI IDE for refactoring across an entire codebase.

Internal tool for team

Greta.sh wins. Team projects with an Owner, Editors, and Viewers, a database on Pro, and one-click deployment. Canvas is for editing code, not hosting a tool your team uses (ChatGPT Sites can host simple team trackers inside ChatGPT).

Generating boilerplate for a project

Greta.sh wins if it's the start of a SaaS project. Canvas works for one-off boilerplate snippets.

Code ownership and portability

Canvas code is exportable from chat (copy to your project). Useful for single files; tedious for multi-file work. Greta.sh exports clean, portable Next.js code, and the Pro plan adds version control with GitHub, so you have a standard project ready for collaboration and deployment. For production work that matters; for snippets, Canvas's copy-paste works.

Pricing comparison

• ChatGPT Canvas: made available to Free and paid users in December 2024; since May 28, 2026 it is only on legacy models for paid users, until those models are sunset
• Greta.sh, as of October 2026: free plan with 5 credits a day; Starter $5/month welcome offer (normally $20/month) for 100 credits; Pro $20/month welcome offer (normally $50/month) for 250 credits
• Different categories with different pricing models
• Not really comparable on price because they don't substitute for each other for serious projects

Common Mistakes

• Trying to build a real SaaS in Canvas: it edits code in a panel and doesn't host apps. Use an app builder.
• Dismissing Canvas as not useful --- It's genuinely good for the work it's designed for.
• Comparing them as equivalents --- Different categories. Different jobs.
• Treating Canvas output as production-ready --- It's a working artifact; not a complete app.
• Overinvesting in Canvas for projects that should be in Greta.sh --- Wasted effort that needs rebuilding.
• Treating Greta.sh output as Canvas --- Greta.sh apps need real production discipline; Canvas snippets don't because they're ephemeral.
• Choosing 'ChatGPT' as a tool --- ChatGPT is the product; Canvas is one capability. Don't confuse the layers.
• Forgetting chat-based editing as a useful tool: it's easy to default to an app builder even for tasks where a chat code block would be faster.
• Planning around canvas long term: OpenAI removed canvas from GPT-5.5 Instant and GPT-5.5 Thinking on May 28, 2026, and paid access runs only through legacy models until they are sunset.
• Using Canvas for client deliverables --- Clients usually need apps they can access; Canvas can't deliver that.

Frequently Asked Questions

Q1: Will ChatGPT Canvas evolve to support full apps? Not on its current path. On May 28, 2026, OpenAI said canvas is no longer available in GPT-5.5 Instant or GPT-5.5 Thinking: writing and coding now happen in chat through writing blocks and code blocks, and paid users can keep canvas on legacy models until those models are sunset. For building and publishing sites and apps, OpenAI now offers ChatGPT Sites (public beta on eligible Plus, Pro, Business, Enterprise, and Edu plans), which hosts sites with built-in storage, optional Sign in with ChatGPT, and custom domains.

Q2: Can I take Canvas output and turn it into a real app? Yes, with significant work. Canvas code can be exported and used as a starting point. But you'd need to add a database, deployment, and a multi-file project structure, essentially rebuilding it as a production app. For a new project, it's usually simpler to start in an app builder like Greta.sh directly.

Q3: What about using ChatGPT API for building real apps? The API is the underlying capability. To ship a real app you still need a tool layer (an app builder or an AI IDE) or custom development to orchestrate everything. Greta.sh lists OpenAI among its connectors, so apps you build there can call OpenAI models.

Q4: Does Greta.sh use ChatGPT under the hood? That isn't something this comparison can confirm. What greta.sh does list is connectors (OpenAI, Claude, Gemini, xAI, and others) that the apps you build can use. Judge it by output quality.

Q5: For someone learning to code, which is better? Chat code blocks (or canvas, where still available) for early learning and experimentation: working with the model on small code, understanding patterns. Greta.sh when ready to build real projects. One path is to experiment in chat, then move to Greta.sh for portfolio projects and actual apps.

Q6: Can I use Canvas for code review? Yes, where canvas is still available to you (paid plans, legacy models): paste code into canvas and use the review code shortcut, and the model suggests changes inline. On newer models, paste the code into chat and ask for a review. Useful for solo review or as a second opinion. Limited compared to full code review tools but valuable for indie founders.

Q7: What about ChatGPT Code Interpreter / Advanced Data Analysis? Different again. Advanced data analysis runs Python for data tasks. Canvas could also run Python (added December 2024), but its focus was collaborative editing. Both useful for different jobs; neither replaces a full app builder.

Conclusion

• Greta.sh and ChatGPT Canvas are in different categories despite both being 'use AI to write code.' Canvas is collaborative code editing within ChatGPT, now limited to legacy models for paid users. Greta.sh is AI app generation with exportable Next.js code and one-click deployment.
• Canvas wins for: working on existing code, prototyping snippets, learning, refactoring isolated code, code review, single-file utilities.
• Greta.sh wins for: building web apps, internal team tools, customer-facing apps that need a database, and deployable applications.
• Workflow can combine both. Chat code blocks or Canvas for prototyping ideas; Greta.sh for the build and deployment; Cursor or similar for ongoing maintenance.

Match the tool to the job. Working on a snippet, learning, or refactoring isolated code? Chat-based editing is fast. Building a web app you'll deploy for real users? Greta.sh is in the app-builder category. They complement each other in a developer's workflow. Use each where it fits. The expensive mistake is forcing the wrong tool: trying to build a SaaS in Canvas, or trying to do snippet-level collaborative editing in Greta.sh.