SupraBench: New Benchmark Evaluates AI Language Models on Supramolecular Chemistry Tasks
A team of researchers has released SupraBench, the first benchmark designed to systematically evaluate large language models (LLMs) on supramolecular chemistry reasoning tasks such as binding affinity prediction and solvent identification. The work addresses a gap in AI evaluation tooling for host-guest chemistry, a field where experimental verification of candidate pairs can take days. The benchmark reveals that current LLMs leave substantial room for improvement across all tested tasks, highlighting specific reasoning gaps in this specialized domain.
Researchers have introduced SupraBench, a benchmark developed in collaboration with domain experts to evaluate LLMs across four core supramolecular chemistry tasks: binding affinity prediction, top-binder selection, solvent identification, and host-guest description, along with an auxiliary vision-based molecular identification task. The benchmark targets a practical bottleneck in the field — designing host-guest systems currently requires days of dry-lab verification per candidate pair, and LLMs have been proposed as a faster alternative. Alongside the benchmark, the team releases SupraPMC, a curated 16-million-token corpus of supramolecular chemistry literature drawn from Europe PMC, intended to support domain adaptation of LLMs. Testing across a broad range of open and proprietary models shows that domain-adaptive pretraining on SupraPMC improves in-distribution regression performance but introduces trade-offs with strict output formatting requirements. Difficulty profiles varied sharply across task families, exposing distinct failure modes that point to specific gaps in how current LLMs reason about supramolecular systems. Both the benchmark datasets and source code have been made publicly available.
What's missing
The paper does not report baseline human expert performance on the benchmark tasks, making it difficult to contextualize how large the gap between current LLMs and domain specialists actually is.
What different sources said
- arXiv cs.AICenter
SupraBench: A Benchmark for Supramolecular Chemistry
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