Browser Tasks in Moss Inference and a New High Score on BU Bench V2.1

Moss Inference is developing a Tasks API that aims to let developers delegate browser-based research and multi-step workflows by supplying a task and context, while the system manages navigation, recovery, verification, and evidence-backed results. Its latest browser-agent configuration scored 84.4 out of 100 across all 200 Browser Use Bench V2.1 tasks, exceeding the published leaderboard high of 79.6 on a shared 180-task subset, while using 17% fewer agent steps than its preceding configuration using the same model. The company also reports a 94% pass rate on Browser Use Bench V1, 99.3% on Online-Mind2Web, an 84.5% perfect-task rate on Odysseys, and a 74.2 score on Odysseys 2, while noting that differing judges, task limits, evidence setups, and evaluation methods complicate direct comparisons with vendors. Moss attributes its browser execution performance to combining frontier models with procedural rules, retrieved guidance for common browser interactions and error recovery, requirement tracking, evidence preservation, and final-answer checks. The system remains in private beta, with the API interface still under development and further testing needed to assess whether benchmark-driven improvements generalize to new real-world workflows.

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