GPT-Realtime-2
GPT-Realtime-2 is OpenAI’s voice model for live interactions where the model can keep the conversation moving while it reasons through requests, calls tools, handles corrections or interruptions, and responds in a way that fits the moment. It is built for a new class of voice apps that feel more natural, respond more intelligently, and take action in real time. GPT-Realtime-2 brings GPT-5-class reasoning to voice experiences, helping agents understand what someone means, track context, recover when a request changes, use tools while the conversation continues, and carry the conversation forward naturally. Developers can enable short preambles like “let me check that” so users know the agent is working, and the model can call multiple tools at once while making actions audible with phrases like “checking your calendar” or “looking that up now.” It also has stronger recovery behavior, longer context for agentic workflows, better retention of specialized terminology, etc.
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Cartesia Sonic-3.5
Sonic 3.5 is Cartesia’s fastest, most natural text-to-speech model, built for expressive, real-time voice generation with sub-90ms latency and native support for 42 languages. It is designed to follow transcripts faithfully, voice confirmation codes, and heteronyms correctly without preprocessing, and stay expressive enough to carry a real conversation. It supports languages intended to deliver native-quality speech. Sonic 3.5 focuses on clean audio across every language and voice, with no artifacts to edit out, making it practical for production voice experiences where quality, speed, and consistency matter. Its expressive conversational delivery provides strong pacing and real emotional range, tuned for support and agent transcripts. Alphanumerics such as order numbers, phone numbers, IDs, and emails are spoken naturally in every language, while context-aware English pronunciation helps words like read, bass, and bow land correctly from the surrounding text.
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GPT-Realtime-2.1
GPT-Realtime-2.1 is OpenAI’s reasoning model with tool use for low-latency voice agents and complex speech-to-speech workflows. It updates GPT-Realtime-2 with improved alphanumeric recognition, silence and noise handling, and interruption behavior, helping applications understand spoken code, manage imperfect audio, and respond more naturally when users pause or talk over the agent. Developers can configure reasoning effort to balance deeper thinking against latency and output usage, while strong instruction following helps the model stay aligned with a defined role, tone, and workflow. It accepts and produces both audio and text, can take images as input, and supports function calling so an agent can retrieve information or perform actions during a conversation. The model has a 128,000-token context window, supports up to 32,000 output tokens, and includes reasoning-token support for extended interactions.
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Cartesia Sonic-3
Cartesia Sonic-3 is a real-time, streaming text-to-speech (TTS) model designed to generate ultra-realistic, expressive voice output with extremely low latency, enabling AI systems to speak as fluidly as humans in live interactions. Built on advanced state space model architecture, Sonic delivers high-quality speech while achieving near-instant response times, with audio generation beginning in as little as 40–100 milliseconds, making conversations feel seamless rather than delayed. It is optimized for conversational AI use cases, acting as the “voice layer” for AI agents by converting text into natural-sounding speech that includes emotional nuance such as excitement, empathy, or even laughter. It supports more than 40 languages with native-level voices and accent localization, allowing developers to build globally accessible applications with consistent quality across regions.
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