Agents' Last Exam: Frontier AI Agent Benchmark
ajratner · x · 2026-07-12
Agents' Last Exam (ALE) is a new benchmark designed to evaluate how frontier AI agents perform on real-world, long-horizon tasks.
- Benchmark Features: Includes 1500+ expert-sourced tasks covering 55 non-physical professions, contributed by over 300 experts from more than 100 institutions.
- Evaluation Method: All tasks are based on actual expert work and are assessed using fully verifiable, outcome-based scoring criteria.
- Industry Application: This benchmark is becoming a key reference in frontier agent development; OpenAI's new model (the tweet mentions GPT-5.6) has shown strong performance on it.
Related event: ICML 2026 Highlights ALE Benchmark and Agent Privacy(4 posts)→
More from Models
- Kimi K3.1 Pro tops MathArena open models, closing frontier gap to about 6 months — teortaxesTex · 2026-10-26
- Ruff creator Charlie Marsh: frontier models find infinite bugs in any software — charliermarsh · 2026-10-26
- Dev testing one skill across Opus 5.5 and Sol 6.1 finds instruction following 'all over the map' — lucasmeijer · 2026-10-26
- supermemory unveils learner-1, claiming continual learning for any model — julianweisser · 2026-10-26
- Anthropic says Opus 5.5 cuts cost per task by ~40% vs Opus 5 — taufiqintech · 2026-10-26
- AI search APIs ranked: top 12 within 7 points, yet prices differ nearly 7x — FinanceYF5 · 2026-10-26