All Competitors

Plant genome foundation model for ab initio gene structure annotation, predicting genes, coding sequences, and exons at single-nucleotide resolution.

Genomic language model from Radical Numerics with a 2 Mbp context window, built for zero-shot variant effect prediction and sequence design.

Genomic foundation model with 120M parameters that learns adaptive DNA token boundaries by dynamic chunking, not fixed k-mer or byte-pair tokens.

DNA language model combining Mamba state-space layers, gated dilated convolutions, and Fourier attention to capture multi-scale regulatory patterns.

Long-context RNA foundation model that predicts splicing, isoform abundance, and variant effects from 64 kb of unspliced pre-mRNA sequence.

Long-context plant DNA language model, 676M parameters on a Mamba2 backbone, pretrained on 65 angiosperm genomes for cross-species variant annotation.

Hybrid framework that predicts ribosome location profiles from mRNA sequence alone, pairing a structure-aware TASEP simulation with a Mamba polisher.

Single-cell foundation model combining regulatory network priors with a Mamba backbone for clustering, batch integration, and perturbation modeling.

Generative foundation model that produces atom-level molecular dynamics trajectories for protein monomers and protein-ligand complexes.

Protein backbone design model pairing flow matching with a Mamba state-space backbone, generating long proteins in linear time with exact geometry.

Genomic foundation model for Cypriniformes fish, built on a Mamba-2 state space model with a 32 kb context window for long-range genome modeling.

EEG-to-text foundation model that turns raw recordings into clinically grounded natural-language narratives instead of fixed-label classifications.

Small-molecule drug discovery foundation model covering ADMET, retrosynthesis, drug-target activity, and molecular optimization in a 2.6B checkpoint.

Tokenizer-free genomic foundation model that adaptively chunks raw nucleotides, enabling zero-shot variant fitness and gene essentiality prediction.

Plant genome foundation model pairing a bidirectional Mamba backbone with sparse Mixture-of-Experts, pretrained on 25.4B nucleotides from 42 species.

Pan-cancer single-cell foundation model with a hybrid Transformer-Mamba architecture, released with the PanFoMaBench cancer evaluation benchmark.

Bidirectional state-space (Mamba-2) genomic model for ultra-long extrachromosomal circular DNA, scaling linearly with sequence length.

Multimodal foundation model that distills Evo 2 into a compact encoder guided by Hi-C data, predicting cell-type-specific 3D genome architecture.

Protein-protein docking scorer that ranks interface poses from image-encoded patches, swapping PIsToN's Vision Transformer for Vision Mamba.

Cryo-EM and cryo-ET map enhancement model that sharpens density maps with a Mamba-based dual-branch UNet and local resolution-guided learning.

Protein language models trained on billions of natural and synthetic sequences for de novo design and zero-shot mutation-effect prediction.

Apple's foundation model trained on behavioral signals from wearables, modeling 27 HealthKit metrics to improve predictions across 57 health tasks.

Spatiotemporal foundation model that learns representations directly from 4D functional MRI volumes for disease diagnosis and phenotype prediction.

Single-cell DNA methylation foundation model capturing genome-wide CpG dependencies in whole-genome bisulfite sequencing across tissues and species.