Google Gemini is currently experiencing a significant outage, affecting users worldwide. The issue began around 6:10 am ET on June 10, 2026, with many users reporting that the AI chatbot is inaccessible. This outage has lasted for over six hours, causing frustration among users and raising questions about the reliability of AI services. Google has acknowledged the problem and stated that its engineers are working on a fix, but an ETA has yet to be provided.
The outage is causing various error messages, including "Error 1099" and "Error 1076," which are server-side issues. These errors often occur during temporary Google server outages or when a specific chat thread becomes overwhelmed. Users are advised to try workarounds such as starting a new chat, logging out and logging back in, or using an alternate account to bypass the issue.
The impact of the outage extends beyond Gemini, as some users are also experiencing issues with other Google products, including Google Docs and Google Drive. This widespread disruption highlights the interconnectedness of Google's services and the potential consequences of a single point of failure.
The timing of the outage is particularly unfortunate, as Google recently unveiled Gemini 3.5 Flash at its annual Google I/O developer conference. This new version of Gemini is designed to execute multi-step workflows and handle longer-running tasks with less human oversight, marking a significant step towards agentic AI.
The prolonged nature of the outage has sparked concerns among users, especially those who rely on Gemini for their work. Some users are even questioning whether they should depend on AI services, given the potential for disruptions. Google's ongoing silence beyond the status page has further fueled frustration, with users demanding more transparency and communication.
As the situation unfolds, users are encouraged to share their experiences and seek workarounds to continue using Gemini. The impact of this outage extends beyond individual users, raising questions about the reliability and resilience of AI services in the face of technical challenges.
