Boson AI’s Higgs Realtime scores higher than GPT and Gemini in interruption recovery
Boson AI’s Higgs Realtime, an audio-native speech-to-speech model, outperformed competitors in handling conversational interruptions. In Boson’s IHBench benchmark, it scored 71.2 on recovery quality, ahead of GPT Realtime 1.5 (65.5), GPT Realtime 2 (62.4), and Gemini 3.1 Flash Live (61.1). The model’s strength lies in real-time processing, where it adapts to mid-conversation changes—like…
Key points
- Boson AI’s **Higgs Realtime** scores **71.2** on interruption recovery, ahead of GPT and Gemini models in IHBench benchmark
- Model supports **100+ languages**, including mid-conversation language switching, with real-time audio processing for natural interactions
- Boson’s system handles **live customer calls** for an insurance company at **1/3 human agent cost**, improving quality from **30 to 80** over five months
Boson’s approach contrasts with traditional pipelines (speech recognition → language model → text-to-speech) by treating audio as a unified input/output stream. Co-founder Alex Smola, who previously led AI initiatives at AWS and researched at Carnegie Mellon University, emphasizes inference economics and multilingual consistency as key differentiators. The company’s ProactBench research explores proactive assistance (e.g., suggesting remote appointments if a user mentions mobility limitations), but Smola stresses balancing anticipation with user control. Boson claims its system handles thousands of concurrent calls for a global insurance company at one-third the cost of human agents, with conversation quality improving from 30 to 80 over five months—far exceeding GPT-4o Realtime’s 55 on the same metric.
Alex Smola, Co-Founder of Boson AI
Unite.AI · 3 November 2026
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