This was originally found in leaked code and promoted by AI influencers on
Imagine adding ChatGPT as another member of your existing group chat, allowing you to text it to your friends or family members and they can respond, and you’ll get an idea of the interesting power and potential of this feature.
However, the feature is currently available as a limited pilot for ChatGPT users in Japan, New Zealand, South Korea, and Taiwan (all tiers including free access).
“Group chat is the beginning of ChatGPTT becoming a shared space to collaborate and interact with others,” OpenAI wrote in its announcement.
The development is based on internal experimentation at OpenAI, where technical employee Keyan Zhang said in a post on X that OpenAI’s team initially considered multiplayer ChatGPT “a wild, out-of-distribution idea”.
According to Zhang, the model’s performance in those early tests demonstrated capabilities far greater than existing interfaces.
The move follows OpenAI investor yet competitor Microsoft’s update to its CoPilot AI assistant to allow group chats last month, as well as Anthropic’s introduction of shareable context and chat history from its cloud AI models via a project feature introduced in summer 2024, though not simultaneous, real-time group chats in the same way.
Integrated collaborative functionality in ChatGPT
Group chats act as shared conversation spaces where users can plan events, brainstorm ideas, or collaborate on projects with the added support of ChatGPT.
These conversations are separate from individual chats and are excluded from ChatGPT’s memory system – meaning that none of the data from these group threads is used to train or personalize future conversations.
Users can start a group chat by selecting the people icon in a new or existing conversation. Adding others creates a copy of the original thread, preserving the source dialogue. Participants can join via a shareable link and are asked to create a profile with a name, username, and photo. The feature supports 1 to 20 participants per group.
Each group chat is listed in a new section of the ChatGPT interface, and users can manage settings such as naming the group, adding or removing participants, or muting notifications.
Powered by GPT-5.1 with extended tools
The new group chat feature runs on GPT-5.1 Auto, a backend setting that chooses the optimal model based on the user’s subscription level and prompt.
Functionality like search, image creation, file upload, and dictation is available inside group conversations.
Importantly, the system applies the rate limit only when ChatGPT is returning responses. Direct messages between human users in a group do not count towards the message limit of either plan.
OpenAI has added new social features to ChatGPT to support this group dynamics. The model can respond with emojis, interpret the context of the conversation to decide when to respond, and personalize content generated using members’ profile photos – such as inserting user likenesses into images when asked.
Privacy by default, controls for young users
OpenAI emphasized that privacy and user controls are integral to group chat design. This feature operates independently of the user’s personalized ChatGPT memory, and no new memories are created from these interactions.
Participation requires an invite link, and members can always see who is in the chat or leaving at any time.
Users under 18 are automatically protected from sensitive content in group chats. Parents or guardians can completely disable group chat access through the built-in parental controls.
Group creators retain special permissions, including immunity from deletion by others. All other participants can be added or removed by group members.
A testbed for shared AI experiences
OpenAI frames group chat as an initial step toward rich, multi-user applications of AI, pointing to broader ambitions for ChatGPT as a shared workspace. The company hopes to expand access over time and refine the feature based on how early users engage with it.
Kean Zhang’s post shows that the underlying model capabilities go far beyond the interfaces with which users currently interact. In OpenAI’s view, this pilot provides a new “container” where more of the model’s latent potential can be unleashed.
“Experiences to date show that our models have a lot of room to shine, and current containers only utilize a fraction of their capabilities,” Zhang said.
With this initial pilot focused on a limited set of markets, OpenAI is likely monitoring both usage patterns and cultural fit as it plans broader deployment. For now, the group chat experiment offers users a new way to interact with ChatGPT and with each other in real time, using a conversational interface that blends productivity and personalization.
Developer access: still unclear
OpenAI has given no indication that group chat will be accessible via API or SDK. The current rollout is designed strictly within the ChatGPT product environment, with no mention of tool calls, developer hooks, or integration support for programmatic use. This absence of signaling makes it unclear whether the company views group interactions as a future developer primitive or as a UX feature inherent only to end users.
For enterprise teams exploring how to replicate multi-user collaboration with a generic model, any existing implementation will require custom orchestration – such as managing multi-party context and signals across separate API calls, and merging session state and responses externally. Until OpenAI provides formal support, group chat remains a closed interface feature rather than a developer-accessible capability.
Here is a standalone concluding subsection prepared for the article, focusing on what the ChatGPAT group chat rollout means for enterprise decision makers in the pilot regions and globally:
Implications for Enterprise AI and Data Leaders
For enterprise teams that are already leveraging – or preparing to leverage – AI platforms – OpenAI’s group chat feature introduces a new layer of multi-user collaboration that can transform the way generative models are deployed in workflows. While the pilot is limited to users in Japan, New Zealand, South Korea, and Taiwan, its design and roadmap provide important pointers for AI engineers, orchestration experts, and data leads globally.
AI engineers managing large language model (LLM) deployments can now begin to conceptualize real-time, multi-user interfaces not only as support tools, but as collaborative environments for research, content creation, and ideation. This adds another frontier in model tuning: not only how models respond to individuals, but how they behave in live group settings with context shifts and different user intents.
For AI orchestration leads, the ability to integrate ChatGPT into collaborative flows without exposing private memory or requiring a custom build can reduce friction in driving generative AI across cross-functional teams. These group sessions can serve as a lightweight alternative to internal tools for brainstorming, prototyping or knowledge sharing – useful for teams limited by infrastructure, budget or time.
Enterprise data managers may also find use cases in structured group chat sessions for data annotation, taxonomy validation, or internal training support. The system’s lack of memory persistence adds a level of data isolation that aligns with standard security and compliance practices – although a global rollout will be important to validate regional data handling standards.
As group chat capabilities evolve, decision makers should monitor how shared usage patterns can inform future model behavior, auditing requirements, and governance structures. In the long term, features like these will impact not only how organizations interact with generic AI, but how they design team-level interfaces around it.