All Competitors

Generative multimodal foundation model that jointly models DNA, RNA, protein, and cellular context across six biological modalities, with SOTA splicing prediction.

A long-context plant DNA language model (676M params, Mamba2) pretrained on 65 angiosperm genomes for cross-species functional annotation.

A fully open structure-guided RNA foundation model pretrained on ~21M RNA sequences paired with secondary structures, enabling robust structural and functional inference.

Google DeepMind model that predicts thousands of functional genomic tracks at single base-pair resolution from megabase-scale DNA sequences. Open-sourced with public API access in January 2026.

Deep learning model predicting cell-type-specific RNA-seq coverage at 32 bp resolution from 524 kb of DNA sequence, jointly modeling transcription, splicing, and polyadenylation.

A 1.6-billion-parameter RNA foundation model pretrained on 42 million non-coding RNA sequences, achieving state-of-the-art performance across 24 of 26 RNA understanding benchmarks.

A BERT-based RNA language model pre-trained on 2M+ pre-mRNA sequences from 72 vertebrate species for splicing prediction and variant effect analysis.