Open Agent Leaderboard
A tiernew this weekA public benchmarking dashboard that ranks AI agents by real-world task performance, accuracy, and cost-efficiency — all in one filterable view.
Kai's verdict
A genuinely useful reference point for the agent benchmarking gap, but it's one institution's snapshot — treat it as a starting signal, not the final word on which agent to bet your stack on. (Verdict pending Phi's full review.)
Strengths
- Ranks agents across multiple benchmarks with filterable dimensions (model, dataset, algorithm)
- Includes accuracy-vs-cost charts, making it practical for budget-conscious teams choosing agents
- Publicly accessible with no sign-up — just open and explore
- Backed by IBM Research, lending credibility to benchmark methodology
Weaknesses
- Coverage limited to agents and benchmarks IBM Research chose to include — not a comprehensive community-wide index
- Leaderboard snapshots can go stale quickly in the fast-moving agent space
- No mechanism described for third parties to submit their own agents for evaluation
Best for
AI researchers, ML engineers, and product teams who need a quick, evidence-based signal on which open agent performs best before committing to a framework.
Pricing
Free
Hosted as a free Hugging Face Space; no account required to browse.