For human evaluators
Evaluator gallery
What the grader scored vs what a human sees. MolBench uses an
escalating grader: a fast scene-tree match, then a pixel-level
visual diff, then a VLM judge for the ambiguous cases.
Tree-match is a deliberately conservative approximation — the
rendered image is the real ground truth. Each card below shows the
reference and the model output with both scores, so you can judge whether the
grader got it right.
STAGE 1
Tree-match
Deterministic F1 over the MolViewSpec scene tree. Fast,
engine-neutral, conservative.
STAGE 2
Visual diff
Pixel/structural similarity of the two renders. Catches
tree-mismatches that look identical.
STAGE 3
VLM judge
A vision model adjudicates the remaining ambiguous cases:
same scene, or genuinely different?
Models: 15 models (spec run, 2026-10-18)
VLM judge: claude-opus-4-8
Rows: 12
Read the featured card first. Its tree scored 0.39 by tree match, yet the scene was judged the same scene by the VLM. Do you agree? The VLM-judged cards are where a human check matters most: the VLM’s verdicts have not yet been validated against human raters.
How cards are picked: 4 per verdict, distinct tasks: lowest tree F1 for rescues, highest tree F1 for VLM-different; ties by model, task.