If you're paying for ChatGPT Plus, Pro, or Teams, you've probably stumbled across both Projects and Custom GPTs and found yourself scratching your head about which one to actually use.
The reality is that Projects and Custom GPTs solve completely different problems, even though they share some overlapping capabilities.
Understanding What These Tools Actually Do
ChatGPT Projects solve organizational chaos. Instead of hunting through dozens of scattered conversations, Projects create dedicated workspaces where you group related chats, files, and instructions. When you start a new conversation within your "Wedding Planning" project, ChatGPT automatically knows about your budget spreadsheets, vendor lists, and specific requirements.
Custom GPTs are specialized AI assistants for specific tasks and sharing with other people. Unlike Projects, which set contextual guardrails, Custom GPTs allow fundamental control over the AI's behavior, logic, and thought process. They can integrate with external services and be shared publicly or with teams.
ChatGPT Projects are currently limited to GPT-4o only, with no option to change models. Custom GPTs are locked to GPT-4 Turbo exclusively. This means Projects have access to the newer GPT-4o model, while Custom GPTs use an older version.
However, there's an important distinction in how customization works: Projects set only "high-level" guardrails through context instructions, while Custom GPTs allow very strict, fundamental changes to the AI's behavior and thought process.
When to use Projects
Projects are great for multi-faceted, evolving tasks where work organization matters more than specialized behavior.
For example, a cross-country move involves researching moving companies, comparing costs, investigating neighborhoods, finding schools, transferring utilities, and dozens of other topics. Without Projects, these conversations scatter across your history. With a "Moving Project," every conversation knows your timeline, budget, family situation, and previous research. You upload moving quotes and school information once, and every chat can reference them.
Ideal Projects scenarios include:
- Complex event planning (weddings, conferences, family reunions)
- Research projects with multiple phases and sources
- Client work where you need separate contexts for different accounts
- Learning new skills where you want to track progress over time
- Home improvement projects with multiple contractors and considerations
Projects also excel for content creators managing multiple distinct projects simultaneously. A marketing consultant can maintain separate projects for each client, ensuring Client A's brand strategy never bleeds into Client B's campaign tactics.
However, there's an important limitation: individual chats within a project cannot reliably reference each other's conversation history. While Projects maintain project-level context (files and instructions), the conversations themselves remain isolated. This means if you discovered something important about venue pricing in Chat A two weeks ago, a new Chat B won't automatically know about that insight unless you manually reference it or convert the conversation to a file.
When to use Custom GPTs
Custom GPTs shine brightest when you need consistent, specialized behavior that goes beyond what standard ChatGPT can provide. Think about a math tutoring scenario. A regular ChatGPT conversation might solve problems correctly, but it won't consistently follow a specific pedagogical approach, maintain the same teaching style, or remember to always check for conceptual understanding before moving to the next topic. A Custom GPT configured as a math tutor can be programmed to always follow specific teaching methodologies, ask clarifying questions in a particular way, and maintain a consistent personality that students become comfortable with.
Custom GPTs use cases:
- Educational tutors with consistent teaching methodologies
- Brand voice assistants that maintain company tone and messaging
- Technical specialists for specific programming languages or frameworks
- Customer service agents trained on company policies and procedures
- Content creators that follow specific style guides or formats
The real magic of Custom GPTs becomes apparent when you start integrating them with external services through APIs. A Custom GPT can be configured to send emails, update your CRM, post to social media, add events to your calendar, or query external databases. Suddenly, you're not just having a conversation with AI—you're giving it the ability to take real actions in the world on your behalf.
Feature Comparison
| ChatGPT Projects | Custom GPTs | |
|---|---|---|
| API Integration | None available | Full API integration support |
| Third-party Tools | No integration capabilities | Works with Zapier, Make.com, HubSpot, Zendesk, etc. |
| Organization | Excellent - dedicated workspaces group related chats | Messy - all conversations mixed in sidebar |
| Context approach | Shared centralized file storage per project (files etc) context shared across all chats in the project | Context not shared across chats. Files tied to GPT configuration |
| Custom instructions | Only high-level guardrails | Very strictly followed |
| External Sharing | Very limited (Teams plans only) | Full sharing via URL links |
| Public Distribution | Not available | Yes, via GPT Store |
| Team Collaboration | No, essentially private workspaces | Excellent - teams can use the same GPT |
| Marketplace Presence | Cannot be listed | Can be published and discovered |
Custom GPTs also excel in team environments where multiple people need to interact with the same specialized AI assistant. Instead of everyone creating their own versions and getting inconsistent results, a shared Custom GPT ensures that your entire team gets the same high-quality, brand-consistent responses. A customer service team can all use the same GPT trained on company policies and FAQ databases, ensuring consistent customer experiences regardless of who's handling the inquiry.
Sharing and collaboration
This brings us to one of the most significant practical differences between these tools: Custom GPTs are built for sharing, while Projects are essentially private workspaces. If you create an amazing Custom GPT that perfectly captures your company's writing style or serves as an expert in your industry, you can share it with colleagues via a simple URL link. You can even publish it to the GPT Store, potentially reaching thousands of users who might benefit from your specialized assistant.
Projects, on the other hand, are locked to your individual account. Even if you're on a Teams plan, the sharing capabilities are extremely limited compared to what Custom GPTs offer. This means Projects work great for personal organization and individual workflows, but they're not designed for collaborative work or team-based projects where multiple people need access to the same resources and context.
The implications of this difference are huge for how you structure your AI workflows. If you're working solo, Projects might be perfect for keeping your work organized. But the moment you need to collaborate with others or share your AI configurations, Custom GPTs become essential.
Memory limitations
Both tools have significant memory limitations that impact real-world usage, though the issues manifest differently.
Projects: Individual chats within a project cannot reliably reference each other's conversation history. This is a major limitation that many users find frustrating. While project-level context (files and custom instructions) is shared across all chats, the conversations themselves remain isolated.
Custom GPTs: Each conversation starts completely fresh with no memory of previous interactions. The GPT knows its instructions and files very well but can't remember yesterday's conversation where you established preferences.
Recent user reports suggest this cross-chat functionality in Projects may have worked better in the past but has become less reliable, with some users reporting it as "broken" since May 2025.
Practical workarounds for memory limitations:
- Convert important chat transcripts to text files and upload them to your project
- Keep a running "insights document" that you update and re-upload regularly
- Use descriptive chat titles to help you find relevant previous conversations
- Summarize key decisions and findings in your project instructions
- Create template prompts that quickly establish context for new chats
Do Gemini and Claude have "Projects"?
ChatGPT isn't alone in offering these features. Google's Gemini has "Gems" (similar to Custom GPTs) for creating specialized assistants. Anthropic's Claude offers "Projects" for organized workspaces.
This convergence across major AI platforms shows these aren't experimental features—they address genuine user needs for both organizational tools and specialized assistants. The strategic thinking you develop around when to use organizational tools versus specialized assistants translates across platforms.
Similar Features Across AI Platforms
| Similar Features Across AI Platforms | Feature Type | ChatGPT | Google Gemini | Anthropic Claude |
|---|---|---|---|---|
| Organizational Workspaces | Projects | ✅ ChatGPT Projects | ❌ Not available | ✅ Claude Projects |
| Specialized AI Assistants | Custom Agents | ✅ Custom GPTs | ✅ Gems | ❌ Not available |
| File Upload Support | Document Analysis | ✅ (with model restrictions) | ✅ | ✅ |
| External Integrations | API Connections | ✅ (Custom GPTs only) | Limited | Limited |
Which should I use?
Given all these considerations, how do you actually decide which tool to use for your specific needs? The decision often comes down to understanding the primary purpose of your workflow and the importance of various features for your particular use case.
Choose Projects when you need:
- Superior organization for complex, multi-session work
- GPT-4o model performance (fixed model)
- Personal workspaces that don't require sharing
- Context that builds and evolves over time
- Clean separation between different work streams
Choose Custom GPTs when you need:
- Deep behavioral modification and control over AI logic
- External integrations and automation capabilities
- Sharing with team members or public distribution
- Highly customized personas or expertise areas
- Repeatable workflows that benefit from consistent performance
If you're working on complex, multi-faceted projects that evolve over time, and you value having access to the latest AI models for general conversation, Projects are probably your best bet. This is especially true if you're working solo and don't need to share your AI configurations with others. The organizational benefits alone can be worth the occasional frustration of switching to GPT-4 Turbo when you need to upload files.
On the other hand, if your work involves highly specialized, repeatable tasks that benefit from consistent AI behavior, or if you need to collaborate with others who should have access to the same AI assistant, Custom GPTs are likely the better choice. This is particularly true if your workflow requires external integrations or if you're building something that others might find valuable enough to use regularly.
For many users, the optimal approach involves using both tools strategically rather than choosing one over the other. You might use Projects for personal organization and file-heavy workflows where GPT-4o's capabilities are sufficient, while maintaining a few key Custom GPTs for specialized work that requires consistent behavior, external integrations, or sharing with others.
Looking Forward
Both Projects and Custom GPTs represent early attempts at solving fundamental challenges in AI interaction, but they're clearly not the final word on these problems. As these tools continue to evolve, we can expect to see improvements that address many of the current limitations and frustrations.
The artificial separation between Projects and Custom GPTs seems particularly ripe for change. There's no obvious technical reason why you shouldn't be able to use a Custom GPT within a Project workspace, combining the specialized behavior of custom assistants with the organizational benefits of project-based workflows. Similarly, the file upload restrictions in Projects feel more like implementation quirks than fundamental limitations, suggesting they could be resolved in future updates.
We're also likely to see significant improvements in memory and cross-referencing capabilities. The ability for chats within a Project to reference each other, or for Custom GPTs to maintain longer-term memory across conversations, would dramatically improve the user experience for complex, ongoing work. These aren't impossible technical challenges—they're more about finding the right balance between functionality, privacy, and computational resources.
Expected improvements in future updates:
- Reliable cross-chat memory within Projects for better context sharing
- Integration between Projects and Custom GPTs in the same workspace
- Model selection options within Projects (currently GPT-4o only, even if the model is showing you can apparently change the model)
- Enhanced sharing and collaboration features for Projects
- Longer conversation memory for Custom GPTs across sessions
- More sophisticated external integrations and automation options
The integration capabilities of Custom GPTs will probably expand as well, with easier ways to connect to popular business tools and services. As AI agents become more sophisticated, we might see Custom GPTs evolve into more powerful automation tools that can handle complex, multi-step workflows across different platforms and services.
