Τ³-Bench is out – can agents handle complex docs and live calls?
τ-Bench is an open benchmark for evaluating AI agents on grounded, multi-turn customer service tasks with verifiable outcomes. It's been great to see the community adopt it since launch — this is now the third iteration. With τ³-Bench, we're extending it to two new settings: knowledge-intensive retrieval and full-duplex voice. τ-Knowledge: agents must navigate ~700 interconnected policy documents to complete multi-step tasks. Best frontier model (GPT-5.2, high reasoning) hits ~25%. The surprising part: even when you hand the model the exact documents it needs, performance only reaches ~40%.…
Τ³-Bench is out – can agents handle complex docs and live calls? launched on March 25, 2026 with 12 votes, #1,060 of 23,380 launches that month and more than 90% of that year's launches.
In plain words
τ³-Bench is an open benchmark for evaluating AI agents on customer service tasks with verifiable outcomes. The third iteration extends testing to two new domains: knowledge-intensive retrieval, where agents navigate approximately 700 interconnected policy documents to complete multi-step tasks, and full-duplex voice interactions with realistic audio conditions like accents and background noise. It targets researchers and developers building AI agent systems, revealing that reasoning over complex, interlinked information and action sequencing—rather than document retrieval—represents the primary performance bottleneck.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
τ-Bench is an open benchmark for evaluating AI agents on grounded, multi-turn customer service tasks with verifiable outcomes. It's been great to see the community adopt it since launch — this is now the third iteration. With τ³-Bench, we're extending it to two new settings: knowledge-intensive retrieval and…
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