CMU got three of Department of @ENERGY Genesis Mission Awards on AI-Enabled Scientific Discovery and the work involving our SMDD-Bench is one of them!! Super excited to continue working on long horizon agents for molecule design!
🧬New agentic AI-for-science benchmark: SMDD-Bench! Can frontier LLM agents actually do small-molecule drug design? Real medicinal chemistry — not single-turn QA, not toy property prediction. Long-horizon, multi-turn, tool-using, with strict oracle budgets. We release 502 agentic tasks across 5 real drug-design workflows (pharmacophore ID, scaffold hopping, lead optimization, fragment assembly, interaction point discovery), every one guaranteed-solvable via a hidden witness molecule. Agents get a Python sandbox, 8 Boltz2 calls, 15 ADMET-AI calls, no internet — and have to plan across dozens of turns to spend that budget wisely. Result: GPT-5.4 and Gemini 3.1 Pro are neck-and-neck at the top (40.2% vs 39.0%), Claude Sonnet 4.6 right behind at 38%. Open-source models trail meaningfully. Even the best agents fail >60% of the time. 🧵 below
https://www.cmu.edu/news/stories/archives/2026/july/carnegie-mellon-researchers-lead-three-doe-genesis-mission-awards-to-advance-the-future-of-ai