Build a JavaScript harness that credits partial progress on long-horizon agent tasks, inspired by SemiAnalysis's GDPx benchmark where the best frontier model tops out at just 12%.
A practical guide to building eval gates that let you swap in cheap open-weight models like DeepSeek, Kimi, and GLM for agent tasks only when task-level accuracy, tool-call reliability, and cost-per-success metrics clear a defined threshold, set against the AI token economy's first deflationary…
A hands-on look at why benchmark wins like Cloudflare's Clef-vs-Jev claim deserve scrutiny, paired with Google's anti-memorization technique and a practical checklist of held-out generation, dynamic task synthesis, and contamination probes for evals that can't be gamed.