Frontier-Bench Released: A New Benchmark for Evaluating AI Agents
ajratner · x · 2026-07-24
The team behind Terminal-Bench and Harbor has released Frontier-Bench, a new benchmark designed to measure and evolve with the frontier of agent work.
The current v0.1 release contains 74 tasks, on which the best AI agents score only about 34%. Snorkel AI contributed to the project as a task author and data partner.
Related event: Frontier-Bench v0.1 Released: Top Agents Score Only 34%(5 posts)→
More from Research
- Open-source decision models sold their own base in Red Alert 2 — then learned until no human could beat them — heathercmiller · 2026-10-27
- DeepMind paper: LLMs can't sample randomly on their own — pass random numbers from code instead — rohanpaul_ai · 2026-10-27
- World Model Assigns Weight and Friction to Objects, Then Simulates with a Physics Engine — jonstephens85 · 2026-10-27
- Token Collapse: Study Finds Graph Soft Prompting Tokens in LLMs Fail to Encode Structure — Sapienza · 2026-10-27
- Mathathon 2.0 launches with Terence Tao's SAIR, $1.5M in compute for teams — _sathvikr · 2026-10-27
- The 'sweet lesson' is real: two kinds of ML problems need opposite strategies — mike64_t · 2026-10-27