How Thinking Machines built interactivity into the model
Thinking Machines has introduced a new model that significantly improves interactivity in AI systems. This model processes audio, video, and text concurrently, allowing for a more natural conversational experience. By eliminating traditional turn-detection components, it enables seamless interaction without artificial boundaries.
- ▪The new model achieves 0.40 seconds end-to-end on the FD-bench V1 benchmark, outperforming competitors like GPT-realtime-2.0 and Gemini-3.1-flash-live.
- ▪It operates on a 200-millisecond tick, allowing for continuous input and output streams without waiting for user turns.
- ▪The interaction model can handle real-time conversations while delegating deeper tasks to a background model, maintaining engagement without interruptions.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3797174) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Thousand Miles AI Posted on May 24 How Thinking Machines built interactivity into the model #ai #llm #machinelearning #news A new release from Thinking Machines, dated May 11, 2026, lands at 0.40 seconds end-to-end on the FD-bench V1 turn-taking benchmark — about three times faster than GPT-realtime-2.0 (xhigh) and roughly half the latency of Gemini-3.1-flash-live (high). The latency number is the surface story.
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