Stanford launches MMBU Challenge, an open VQA benchmark contest for biomedical multimodal AI
LiorOnAI · x · 2026-10-01
Stanford's Medical AI and CV Lab launched the MMBU Challenge, scoring models with open-ended VQA on the expert-curated MMBU biomedical image benchmark across three tracks: frontier, medically adapted, and efficient models under 4B active parameters. Backed by Stanford AI Lab, Anthropic, GXL and Biohub, with credits, cash prizes, and registration until 9/30.
Related event: Stanford and Partners Launch $100K MMBU Biomedical Multimodal Challenge(3 posts)→
More from Models
- Perplexity's new contextual embedding model tops turbopuffer's context-bench with 50%+ recall gain — marktenenholtz · 2026-10-01
- Local LLM Fans Face a Reality Check: 8-10T Parameter Models Will Need a Server Rack — power97992 · 2026-10-01
- Inception launches Mercury Decide, a structured decision model hitting 14 decisions per second — StefanoErmon · 2026-10-01
- OpenAI Gives Daybreak Blue Users One Day to Get a FIDO2 Key or Lose Access — Admirable_Trainer_54 · 2026-10-01
- Experiment restricts Qwen to Wikipedia's 250 most common tokens plus rare ones — cephaloform · 2026-10-01
- Strix Halo Plus R9700 Hybrid Hits 60+ tok/s, Beating DGX Spark on Local LLM Inference — darklordfireape · 2026-10-01