LiteMol-1 is LiteFold's first molecular foundation model for agent-driven design. The benchmark panel summarizes peptide co-fold confidence across ipSAE, ipTM, and pLDDT, plus small-molecule docking strength against public baselines.
| System | Score (score) |
|---|---|
| LiteMol-1 + MCTS | 8.02 |
| ProtoBind-Diff | 8.17 |
| LiteMol-1 | 7.77 |
| PocketXMol | 7.18 |
MitoTox is LiteFold's state-of-the-art model for mitochondrial toxicity prediction, part of our pre-clinical stack (Signal). It helps teams screen liabilities early and run toxicity-aware lead design and optimization.
| System | Score (%) |
|---|---|
| MitoTox (LiteFold) | 82.6 |
| Atom-Pair + GB Baseline | 80.9 |
| Mammoth (LiteFold) | 39.5 |
STMV benchmark (1.07M atoms, explicit PME), higher is better. Our optimized engine brings datacenter-class molecular dynamics throughput to a single RTX 5090, measured in nanoseconds simulated per day. Representative benchmark comparing our engine against stock OpenMM and datacenter GPUs.
| System | Score (ns/day) |
|---|---|
| RTX 5090 (LiteFold) | 136 |
| B200 | 118 |
| RTX 5090 (Stock) | 101 |
| H200 | 78 |
| H100 | 62 |
| RTX 4080 | 46 |
| A100 | 32 |
BixBench is the Future House benchmark of 200+ real bioinformatics tasks built from published research notebooks. Agents have to navigate complex datasets, execute Python and R, generate testable hypotheses, and defend their answers. New re-evaluations are ongoing right now, and the leaderboard will be refreshed as results finish.
| System | Score (%) |
|---|---|
| Rosalind (LiteFold) | 90.24 |
| K-Dense | 90.0 |
| Biomni Lab | 88.7 |
| Edison | 78.0 |
| Claude Code (Opus 4.6) | 65.3 |