ChatGPT Projects vs Custom GPTs (Updated Nov 2025)

At A.CRE, we’re always on the lookout for tools that can streamline our workflow and make our jobs a little easier. As the AI space evolves, OpenAI has rolled out two features that we’ve been putting to work in our day-to-day operations: ChatGPT Projects and Custom GPTs.

These two features have unlocked new ways for our team to stay organized and improve productivity, but they serve very different purposes. With Projects, we’re able to keep our research, models, and ongoing discussions for each initiative neatly organized in one place. Meanwhile, Custom GPTs allow us to create specialized AI tools—like our A.CRE AI Assistant—that are tailored to specific tasks.

Since we’ve been getting a lot of questions about the difference between these two features, I figured it was time to break it down for our readers. So, whether you’re an AI novice or a GPT power user, this post will walk you through the key differences, use cases, and best practices for ChatGPT Projects vs. Custom GPTs.

1. Purpose: Organizing Projects vs. Creating AI Assistants

The primary difference between ChatGPT Projects and Custom GPTs is their purpose.

• ChatGPT Projects: Used for organization. Think of them as dedicated workspaces where you can store related chats, files, and instructions for a specific task or workflow.
• Custom GPTs: Used for customization. These are tailor-made AI assistants designed to perform highly specific tasks, like financial modeling assistants or AI research analysts.

In short: Use ChatGPT Projects to keep your work organized. Use Custom GPTs to build specialized AI tools.

2. Customization: Guardrails vs. AI Behavior

Another key difference is the level of control and customization you have with each tool.

• ChatGPT Projects: Set high-level guardrails like context instructions. You can provide the AI with context, but you cannot fundamentally change how the AI behaves.
• Custom GPTs: Full control over the AI’s behavior, logic, and prompt. You can adjust how it responds, create specific task-based logic, and even control what external tools it can access.

In short: ChatGPT Projects let you set project-level context, while Custom GPTs let you fully control the AI’s thought process.

3. AI Models: Different Models, Different Capabilities

• ChatGPT Projects: Offers a variety of models, including GPT-4o, 4o-Mini, 4, o1, and o1-Mini. Users can select the best model based on speed, cost, and performance needs.
• Custom GPTs: Uses GPT-4-turbo with the ability to customize its behavior and logic via prompt engineering.

In short: ChatGPT Projects offer you multiple model options, while Custom GPTs use a single model but allow full customization of its behavior.

4. Customization of the AI’s Core Prompt

• ChatGPT Projects: No prompt customization. Context is set at the project level, but the AI logic remains the same.
• Custom GPTs: Full control over the prompt. You can define what the AI “knows” and how it “thinks,” allowing for powerful, task-specific AI tools.

5. API and Tool Integrations

• ChatGPT Projects: No external API or tool integration. However, you can use image generation, web browsing, and Advanced Data Analysis (ADA) within the project.
• Custom GPTs: Full API access and tool calling. Custom GPTs can integrate with third-party platforms, databases, and automation platforms like Make.com and Zapier.

In short: ChatGPT Projects access internal tools like web search and image generation, while Custom GPTs can trigger external APIs and interact with third-party platforms.

6. Sharing and Collaboration

• ChatGPT Projects: Not shareable. Projects are private workspaces accessible only by the account owner.
• Custom GPTs: Shareable and distributable. You can publish them in the GPT Marketplace or share links with teammates or clients. For instance, you can access the A.CRE library of custom GPTs whereas you can’t see the Projects we use internally.

7. Best Use Cases for Each Tool

Tool	Best Use Cases
ChatGPT Projects	Trip planning, research projects, workspaces, ongoing projects
Custom GPTs	AI tutors, customer service bots, domain-specific assistants

8. Analogy: The Lecture Hall and the Professor

Here’s a simple way to think about the difference between the two tools:

• ChatGPT Projects are like a lecture hall. Students (chats) are organized neatly, each with access to laptops (advanced data analysis) and notebooks (files). If you leave the room, the students, laptops, and notes stay behind.
• Custom GPTs are like the professor in the lecture hall. The professor is a domain-specific expert (chemistry, real estate, Shakespeare) and can call on external tools to deliver better lectures. This professor can give lectures in multiple halls at once, each customized for its audience.

9. Key Differences Recap

Feature	ChatGPT Projects	Custom GPTs
Primary Purpose	Organize files, chats, and instructions	Create specialized AI assistants
AI Models	GPT-4o, 4o-Mini, 4-turbo, o1, o1-Mini	GPT-4-turbo
File Organization	Yes	No
Tool Calling	No	Yes
Sharing	No	Yes

Final Thoughts

Both ChatGPT Projects and Custom GPTs have become essential tools in our workflow at A.CRE. We use Projects to keep our files, chats, and context organized for ongoing deals and research. Meanwhile, Custom GPTs help us create specialized assistants for underwriting and automation.

Hopefully, this breakdown helps you understand when to use a Project and when to build a Custom GPT. Happy AI building!

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Frequently Asked Questions about ChatGPT Projects vs Custom GPTs

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