Handshake AI’s VIALS benchmark gets an independent leaderboard, and the results reveal a 99x cost gap between top models

Artificial Analysis' VIALS-AA ranks vision-language models on scientific image interpretation, exposing wide performance and pricing gaps across leading AI systems. Reading a gel blot or interpreting a microscopy image requires the kind of domain knowledge that takes researchers years to develop. VIALS-AA, launched by Artificial Analysis on November 6, 2026, is a direct attempt to close that measurement gap. The leaderboard is an independent implementation of Handshake AI’s VIALS benchmark, built specifically to stress-test vision-language models on life sciences and biotech imagery: gel blots, molecular structures, microscopy slides, and similar artifacts that show up constantly in real research workflows but almost never in standard AI evaluations. Who’s leading and what it costs them Across 161 visual question-answering tasks, Gemini 4 Carbon (high) currently holds the top position with a score of 64%, measured as the proportion of tasks answered correctly across three repeated runs. GPT-6 Astra (max) sits just behind at 63%, with Claude Opus 5.5 (max with fallback) at 61%. GPT-6 Luna (max) completes the full task set for $0.02. Grok 4.7 (xhigh) runs the same gauntlet for $1.77....