AI systems can now write code, pass professional exams, and assist with scientific research, and their capabilities are improving remarkably fast. But measuring exactly what AI can and cannot do is genuinely difficult, with benchmarks struggling to keep pace and real-world performance often diverging from test scores. Epoch tracks AI capabilities across tasks and benchmarks, examining how fast progress is happening, how predictable it is, and what it reveals about where the technology is heading.


Our hub for benchmark results, featuring the performance of leading AI models on challenging tasks. It includes results from benchmarks administered internally by Epoch AI as well as data collected from external sources. Explore trends in AI capabilities across time, by benchmark, or by model.

AI model scores on Epoch AI's IKEA furniture assembly benchmark jumped from 28% to 80% in 10 months, with open-weight models trailing closed-weight models by about 7 months. Epoch AI's test of visual and spatial reasoning across 60 photos from three furniture builds.

Epoch AI measures how fast the cost of a given level of AI performance is falling across five benchmarks covering math, science and games of skill: about 47% per quarter, or 13x per year, since 2023, faster than electricity, compute, batteries or DNA sequencing ever fell.

OpenAI's GPT-6 Astra tops the Epoch Capabilities Index (ECI) with a score of 166, ahead of Claude Fable 5.1 at 164 and GPT-5.6 Sol at 162. Its Math-ECI of 170 sets a new record, but on software engineering benchmarks its SWE-ECI of 164 still lags behind Fable 5.1's 167.


A benchmark of 68 significant Erdős problems, open as of August 2026, curated by Thomas Bloom and formalized in Lean. AI systems must prove or disprove them within a fixed budget.

A good benchmark asks more than just “can AI do this specific task?”

Notable organizations disclosed ~2,500 high- and critical-severity CVEs in July 2026, about 5× the pre-Mythos monthly record. Epoch AI's updated breakdown of vulnerability disclosures following Anthropic's Project Glasswing.

Expert assessments and cyber benchmarks led us to expect that frontier models were capable of executing this kind of cyberattack

We tested Pangram, GPTZero, and Originality.ai on human and AI text. All three caught nearly every passage written from a simple prompt, but missed roughly one in five passages imitating a specific author's style.