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OpenAI releases GPT-Live-1.1 voice model with full-duplex support

OpenAI launched GPT-Live-1.1 and GPT-Live-1.1 Quip on October 15, 2026, marking the next iteration of its voice AI models. The key innovation is full-duplex capability, enabling simultaneous listening and responding to mimic natural human conversation—handling pauses, interruptions, and varying speech rhythms. This replaces the previous GPT-Live-1 mini and will serve as the default voice model…

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Key points

  • GPT-Live-1.1 adds full-duplex voice, responding mid-conversation to match human rhythms
  • Default for OpenAI Plus+ users and integrated into Codex and Dots as of October 15, 2026
  • Safety tests show no regression in real-world prompts but four risk areas worsened in synthetic tests

The system card highlights a two-model architecture: GPT-Live handles voice interaction while delegating complex tasks to a backend model (e.g., GPT-5.6 Terra), inheriting its safeguards. OpenAI’s safety evaluations show no statistically significant regression in production prompts but reveal declines in four risk categories—sexual content, mental health, emotional dependency, and gore—based on synthetic tests. The company notes these are edge cases and plans further research. Alignment tests also show minor variations in adherence to restrictions and deception resistance, though all GPT-Live models outperformed the base model. OpenAI advises deploying voice AI with system-level safeguards, not just model-based ones, and emphasizes separating voice UI design from task delegation.

Full story from note.com · by 【AI最速情報】パープル博士 · via Search: OpenAIOpen source ↗

OpenAI's "GPT-Live-1.1" Arrives! Decoding the Capabilities and Safety Evaluations of Full-Duplex Voice AI

note.com · 16 October 2026

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This text was published by note.com and written by 【AI最速情報】パープル博士. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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