You can find additional information about our pre-deployment evaluation of GPT-5.6 Sol on our website: https://t.co/jvGwK5ljp7
Who's Who of AI
METR
Why they matter
Directory member with public evidence across Evaluation & benchmarks.
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METR is a research nonprofit that builds evaluations to empirically test AI systems for capabilities that could threaten catastrophic harm to society.
What they're sharing
Summary of METR's predeployment evaluation of GPT-5.6 Sol metr.org
Careers at METR metr.org
How independent researchers could investigate AI propensities after misalignment incidents metr.org
Expenditure Horizon: Measuring Optimization Ability, with an Application to NanoGPT metr.org
Articles & links
We are significantly expanding our team and starting new ambitious projects. Join our team to help us realize this opportunity: https://t.co/8XoCmUPJiK.
See our blog for more: metr.org/blog/2026-07...
See the post for more, including: (1) a sketch of what we know about AI-assisted R&D; (2) alternative metrics for optimization ability; (3) estimated returns to human labor in NanoGPT; (4) details on NanoGPT agent runs. metr.org/blog/2026-07...
Their own posts
Recent commentary
We have reached an agreement with OpenAI to conduct an independent review, with Redwood Research, of the model behavior observed during the Hugging Face incident. We will publish a blog post that describes the terms of our engagement, the scope covered, and tentative conclusions.
OpenAI gave METR early access to GPT-5.6 Sol for testing including raw chain-of-thought, a railfree version of the model, and internal information about the model. With this access, METR conducted a pre-deployment evaluation of GPT-5.6 Sol, including an attempted measurement of its 50%-Time Horizon.
Introducing “expenditure horizon”: a proposed method for measuring AI capabilities on continuously-scored problems. The method compares performance as a function of spend for humans vs agents. The point where humans become more cost-effective is the agent’s expenditure horizon.
In the last 6 months, METR raised commitments of around $71 million. This will fund ambitious projects: studying autonomous capabilities, tracking recursive self-improvement, evaluating monitoring systems, conducting risk assessments, investigating AI incidents, and more.
We believe it's important to track and investigate misalignment incidents: cases where an AI agent autonomously took sophisticated, sustained actions in violation of human intent. In a new post, we lay out how independent propensity investigations of such incidents could be conducted.
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