METR assessment finds Anthropic model capabilities accelerating AI research by 1.9 times

Independent evaluation non-profit METR published a high-access risk assessment on 5 November 2026 examining how internal AI usage is accelerating AI research and development inside Anthropic. Conducted between 12 August and 29 October 2026, the audit granted METR researchers access to internal pretraining and reinforcement learning metrics, domain-level training compute logs, unannounced internal model checkpoints (including Opus 5.5, Mythos 5.1 and internal Model 2 through Model 4 snapshots), speedup analyses and staff interviews.

Measured on AECI (Anthropic’s internal version of the Epoch Capabilities Index aggregating public and internal benchmarks), capability growth since October 2025 ran at 1.9 times the March 2024 to October 2025 trend (95% confidence interval: 1.5 to 2.8 times), rising from +15 AECI points per year to +29 points per year.

Attribution to AI assistance and bottleneck outlook

METR concluded with high confidence that the speedup did not come from faster training-compute scaling. Instead, staff surveys, interviews and internal uplift studies attribute a majority of the current ~2 times pace increase (subjective range: 1.3 to 3 times) to extensive AI assistance across engineering, data curation and experiment triage, with early signs of fully autonomous R&D contributions emerging. METR noted it found no clear evidence of algorithmic, compute or data bottlenecks over the next 12 months, while cautioning that key underlying evidence was redacted by Anthropic.