腾讯 Gander：边工作边持续对话

Tencent's Gander is designed to hold real-time conversations while handling complex tasks in the background. It processes speech, images, and text simultaneously, and users can interrupt at any time. A "cerebellum" manages the conversation second by second, while a swappable "brain" handles complex agent tasks. The split aims to keep responses fast without cutting planning short. In tests, Gander interrupted users less often than competing models but trailed on task accuracy and showed weaknesses in video and audio understanding. The team plans to release model weights and training data. A GitHub repository for the code already exists. Tencent's research model Gander combines real-time conversation with AI agent capabilities. A "cerebellum" handles the conversation while a swappable "brain" tackles complex tasks. Users can interrupt at any time, but tests show a tradeoff between conversational timing and task accuracy. Tencent's Hunyuan Speech team and researchers at several universities have introduced Gander, an AI model designed to keep chatting while it handles complex tasks. According to the technical report, it takes in speech, images, and text at the same time. Today's voice assistants mostly take turns with users, the researchers argue . In real conversations, people interrupt each other, give quick feedback, and listen while talking. Gander is designed to handle that back-and-forth by continuously processing video, speech, and text, even while it speaks. Users can jump in at any time, and the model can ask follow-up questions or give progress updates without being prompted. Ad Conversation needs quick responses, but searching files or writing code takes time to plan. The researchers argue that a single model has to balance speed against reasoning ability, so Gander splits the work between two roles. Ad Borrowing from human anatomy, they call these the "cerebellum" and the "brain." The cerebellum handles real-time conversation while the brain tackles reasoning and complex tasks in the background. The brain can be swapped out for agent systems such as Codex or Claude Code without retraining the conversation model. In tests, an unspecified model from OpenAI's GPT-5.6 family filled that role. As the underlying model improves, the whole system benefits. Ad Gander breaks conversations into one-second segments so the cerebellum can decide when to listen, speak, or stop if the user interrupts. It makes those decisions without a separate module to detect when speech starts and stops, using roughly the last two minutes of conversation as memory. With no dedicated test for models like Gander yet, the researchers turned to established benchmarks. The report says Gander had the best timing on Full-Duplex-Bench v3, which tests voice assistants across different task scenarios. Ad Gander starts speaking at the right moment in all 100 scenarios and interrupts users in 8 percent of cases. That compares with 13.5 percent for GPT-Realtime and nearly 48 percent for the weakest competitor. According to the report, Gander uses a relatively small model to compete against commercial systems including GPT-Realtime, Gemini Live , and Grok. Ad