ElevenLabs launches Eleven Realtime: two speech-to-speech models for live voice agents
ElevenLabs introduced Eleven Realtime v1 Mini and v1 Max, complete speech-to-speech voice agents supporting 90+ languages and 17,000+ library voices; it cites Artificial Analysis scores including 98.8% Big Bench Audio accuracy and 0.57s time-to-first-audio for Max.
ElevenLabs’s official blog announces Eleven Realtime, a class of speech-to-speech models in which each model is a complete voice agent—without assembling separate ASR, VAD, turn-taking, LLM, and TTS stacks. Shipping today: v1 Mini for natural conversations at lower cost (assistants, teachers, interactive characters, and most use cases) and v1 Max for complex, process-following workflows (customer support, lead qualification, multi-step tasks). Both support more than 90 languages and any of the 17,000+ voices in the ElevenLabs library.
ElevenLabs cites Artificial Analysis evaluations: on Big Bench Audio (1,000 spoken reasoning questions), v1 Max answered 98.8% correctly and v1 Mini 75.9%; average time to first audio is 0.57s for Max and 0.62s for Mini. On Full-Duplex-Bench (pauses, turn-taking, interruptions, backchannels), Mini scores 95.8% and Max 94.1%. In Speech Agent Arena blind live comparisons, Max scored 998 and Mini 988; on tool-use tasks Max completed 87.1% and Mini 60.3%, which is why ElevenLabs recommends Max for heavy tool calling. Models are selectable in ElevenAgents; the Realtime API uses WebSocket and is described as compatible with OpenAI’s Realtime specs so existing integrations can switch endpoint and model name. Figures are vendor-cited third-party results, not re-measured here.