Back to browse
Open Benchmarks Grants– a $3M commitment to close the AI eval gap

Open Benchmarks Grants– a $3M commitment to close the AI eval gap

by vincentschen·Feb 11, 2026·6 points·0 comments

AI Analysis

PassBold BetBig Brain
The Take

They're putting real cash and infrastructure behind a problem the field keeps kicking down the road: evaluation for agentic systems. The program explicitly targets environment complexity, autonomy horizon, and output complexity, and ropes in sensible partners (Hugging Face, PyTorch, etc.) — that's a practical way to seed meaningful open benchmarks rather than another leaderboard. Missing: concrete application criteria, timeline, and license/reproducibility guarantees, which will determine whether this becomes useful research infrastructure or just noise.

Category
Target Audience

AI/ML researchers, academic teams, open-source contributors, benchmark and dataset builders, evaluation-focused engineers

Post Description

Today, we're launching the Open Benchmarks Grants: a $3M commitment to fund open-source and academic teams building benchmarks for AI agents. In partnership with HuggingFace, PrimeIntellect, FactoryHQ, Together, Harbor, and PyTorch, the grants provide funding, data development support, and research collaboration.

Our ability to measure AI has been outpaced by our ability to develop it, and we believe this evaluation gap is one of the most important problems in AI. Open benchmarks are one of the most important levers for advancing AI safely and responsibly—but the academic and open-source teams driving them often hit resource constraints, especially in the face of the exponentially expanding complexity of what tomorrow’s benchmarks need to cover.

We think the next wave of benchmarks needs to push on three axes: - Environment complexity - How realistic is the operating environment? - Autonomy horizon - How far can an agent operate independently? We need to measure - Output complexity - How sophisticated is the work product?

Happy to answer questions about the grants, the framework, and would love to hear more about what you’re building!

Similar Projects

Nonprofit Results-Based Management logic model skill for OpenClaw

This skill automates the tedious parts of writing program logic models — it outputs a 5-level results chain, an if/then Theory of Change with assumptions, SMART indicators, SDG mapping and a monitoring plan. That feature set is exactly what M&E teams and grant writers want, but the public face is rough (ClawHub shows "Skill not found"), so the project needs clearer example outputs, ready-to-copy indicator templates, and better onboarding to move from useful hobby to everyday tool.

Niche GemSolve My Problem
vassilbek
103mo ago
AI/ML●●●Banger

Grantex – Delegated authorization protocol for AI agents

OAuth-equivalent for agents: cryptographic identity, scoped grants, audit trail.

Zero to OneBig Brain
mishrasanjeev
203mo ago