Boson AI Unveils Higgs Realtime Duplex: A 45B MoE Full-Duplex Omni Model That Listens, Watches, Talks, and Calls Tools in the Background; API Waitlist Open
On 2026-11-05 Boson AI (the team of Mu Li and Alex Smola) released a research preview of Higgs Realtime Duplex: a 45B MoE front model that slices voice, video, and tool results into 160 ms chunks so it can listen, watch, speak, and render its own face at once, while thinking, calling tools, or delegating hard questions to a larger backend model without pausing. Vendor-reported scores include Big Bench Audio 98.9, tau-Voice 69.8, and Full-Duplex-Bench v1.5 75.5. The API is waitlist-only for now; the earlier Higgs Realtime is available today.

Key Takeaways
- Shape: a 45B MoE front model, further trained on about 2T tokens of text, audio, and video; every stream is cut into 160 ms chunks, silence included
- Background work: it thinks and calls tools asynchronously while talking, and delegates hard tasks with full context to a larger backend model (a frontier model is recommended)
- Vendor-reported scores: Big Bench Audio 98.9 (top of the table), IFEval 94.1, tau-Voice 69.8 (GPT-Live-1 about 74.5), Full-Duplex-Bench v1.5 75.5 (GPT-Live-1 80.1, TML 77.8)
- Cost design: audio and video use about 2.6K tokens per minute, about 2.6K-5K with thinking and tools; the target is an hour of talk costing at most one-tenth of an hour of human time
- Availability: the Duplex API is waitlist-only; voice and face swap zero-shot from a reference clip or a single image





