--- license: cc-by-4.0 task_categories: - question-answering language: - en tags: - chemistry - solubility - cheminformatics - llm-benchmark - smiles pretty_name: SoluBench configs: - config_name: task1 data_files: - split: test path: task1_pairwise_solvent_comparison.csv - config_name: task2 data_files: - split: test path: task2_best_solvent_selection.csv - config_name: task3 data_files: - split: test path: task3_cosolvent_effect_prediction.csv - config_name: task4 data_files: - split: test path: task4_pairwise_compound_comparison.csv --- # SoluBench **SoluBench** is a benchmark for evaluating large language models on solubility-related tasks of various complexity. It is built on top of [BigSolDB v2.0](https://www.nature.com/articles/s41597-025-05559-8) and [MixtureSolDB](https://doi.org/10.26434/chemrxiv-2025-m51v8) — two curated experimental solubility datasets. > 📄 Preprint: *coming soon* > 💻 GitHub: [levakrasnovs/SoluBench](https://github.com/levakrasnovs/SoluBench) --- ## Tasks | Config | Task | Description | Input | Output | n | Random baseline | |--------|------|-------------|-------|--------|---|-----------------| | `task1` | Pairwise solvent comparison | Given a compound (SMILES) and two solvents, select the one with higher solubility | SMILES + 2 solvents | A / B | 3699 | 50.0% | | `task2` | Best solvent selection | Given a compound and a list of solvents, select the one with highest solubility | SMILES + N solvents | letter | — | ~17.1% | | `task3` | Co-solvent effect prediction | Given a compound, a base solvent and a co-solvent mixture, predict whether solubility increases or decreases | SMILES + mixture composition | A / B | — | ~16.7% | | `task4` | Pairwise compound comparison | Given a solvent and two compounds (SMILES), select the one with higher solubility | Solvent + 2 SMILES | A / B | 3000 | 50.0% | --- ## Usage ```python from datasets import load_dataset # Load a specific task ds = load_dataset("levakrasnovs/SoluBench", "task1") print(ds["test"][0]) # Load all tasks for task in ["task1", "task2", "task3", "task4"]: ds = load_dataset("levakrasnovs/SoluBench", task) print(f"{task}: {len(ds['test'])} rows") ``` --- ## Data fields ### Task 1 — Pairwise solvent comparison | Field | Description | |-------|-------------| | `id` | Unique row identifier | | `DOI` | Source publication | | `SMILES` | Compound SMILES | | `Temperature_K` | Temperature in Kelvin | | `Solvent_A` | First solvent | | `Solvent_B` | Second solvent | | `LogS_A` | Experimental log solubility in solvent A (mol/L) | | `LogS_B` | Experimental log solubility in solvent B (mol/L) | | `Delta_LogS` | \|LogS_A − LogS_B\| | | `Answer` | Correct answer (A or B) | ### Task 2 — Best solvent selection | Field | Description | |-------|-------------| | `id` | Unique row identifier | | `DOI` | Source publication | | `SMILES` | Compound SMILES | | `Temperature_K` | Temperature in Kelvin | | `Best_solvent` | Solvent with highest solubility | | `Best_LogS` | LogS in best solvent | | `Second_best_solvent` | Solvent with second highest solubility | | `Second_best_LogS` | LogS in second best solvent | | `Delta_LogS_best_minus_second` | LogS difference between best and second best | | `All_solvents` | Semicolon-separated list of all solvents | | `All_LogS` | Semicolon-separated list of all LogS values | | `Answer` | Correct answer (letter corresponding to best solvent) | ### Task 3 — Co-solvent effect prediction | Field | Description | |-------|-------------| | `id` | Unique row identifier | | `DOI` | Source publication | | `SMILES` | Compound SMILES | | `Temperature_K` | Temperature in Kelvin | | `Base_solvent` | Pure base solvent | | `Added_solvent` | Co-solvent added to the mixture | | `Fraction_base` | Fraction of base solvent | | `Fraction_added` | Fraction of added co-solvent | | `New_composition` | Human-readable mixture description | | `Fraction_type` | Type of fraction (mole/volume/mass) | | `Delta_LogS_new_minus_base` | LogS(mixture) − LogS(pure base) | | `Answer` | A = solubility enhanced, B = solubility reduced | ### Task 4 — Pairwise compound comparison | Field | Description | |-------|-------------| | `id` | Unique row identifier | | `Solvent` | Solvent name | | `Temperature_K` | Temperature in Kelvin | | `SMILES_A` | SMILES of compound A | | `SMILES_B` | SMILES of compound B | | `Compound_name_A` | Name of compound A | | `Compound_name_B` | Name of compound B | | `LogS_A` | Experimental log solubility of compound A (mol/L) | | `LogS_B` | Experimental log solubility of compound B (mol/L) | | `DOI_A` | Source publication for compound A | | `DOI_B` | Source publication for compound B | | `delta_logS` | LogS_A − LogS_B | | `Answer` | Correct answer (A or B) | --- ## Source datasets | Dataset | Paper | Download | |---------|-------|----------| | BigSolDB v2.0 | [Nature Scientific Data](https://www.nature.com/articles/s41597-025-05559-8) | [Zenodo](https://doi.org/10.5281/zenodo.15094979) | | MixtureSolDB | [ChemRxiv](https://doi.org/10.26434/chemrxiv-2025-m51v8) | [Zenodo](https://doi.org/10.5281/zenodo.18660057) | --- ## Model results Full model evaluation results (20+ LLMs including GPT, Claude, Gemini, Grok, Qwen, DeepSeek, GLM) are available in the [GitHub repository](https://github.com/levakrasnovs/SoluBench/tree/main/results). --- ## Citation > Citation will be added upon preprint publication. --- ## License [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)