All Competitors

Multimodal reasoning LLM for protein function prediction, fusing protein language model embeddings to emit interpretable GO-term reasoning traces.

Molecular reasoning model built on DeepSeek-7B, using chain-of-thought and reinforcement learning for property prediction, generation, and reactions.

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

Large language model trained on functional genomics data to prioritize novel therapeutic targets from genome-wide CRISPR knockout screens.

Longitudinal chest X-ray vision-language model that reads a follow-up radiograph against its prior study and forecasts how findings will change.

Healthcare reasoning model for symptom triage, wellness planning, and clinical workflows, post-trained with rubric-based reinforcement learning.

Vision-language foundation model linking human brain activation maps and neuroscience text for text-to-brain and brain-to-text generation.

Connects a frozen protein language model to a general LLM via a cross-modal projector, adding protein reasoning without catastrophic forgetting.

Cross-modal single-cell foundation model that aligns gene-expression profiles with LLM-enriched cell descriptions in a shared embedding space.

Antibody developability predictor pairing text and protein language models, using in-context learning to fit new assays without retraining.

Gut microbiome foundation model pretrained on human shotgun metagenomes, learning species-level taxonomic representations for disease prediction.

Transformer foundation model pretrained on a biomedical knowledge graph for zero-shot drug repurposing, target, and adverse-effect prediction.

3D vision-language foundation model for abdominal CT, pretrained on scans, radiology reports, and EHR codes for zero-shot interpretation.

Prokaryotic genome language model that reads annotated replicons as ordered gene-product descriptors to predict plasmid hosts and gene essentiality.

Conversational single-cell and spatial multi-omics brain foundation model, with zero-shot cell annotation and disease prediction across species.

Antibody language model pretrained only on CDR-H3 loops, giving embeddings for immune repertoire analysis and antibody sequence classification.

Multimodal EHR foundation model that fuses polygenic risk scores into a GPT-2-style backbone by cross-attention for zero-shot disease risk prediction.

Clinical laboratory morphology vision-language model that identifies cells, describes them and localizes them in blood, urine and stool microscopy.

Multimodal LLM that tokenizes single cells into discrete VQ-VAE codebook tokens, letting one model reason jointly over transcriptomes and text.

Multimodal molecular large language model grounding molecule understanding and generation in fine-grained, multi-level chemical knowledge.

Medical vision-language model that takes visual prompts on an image and returns answers grounded in pixel-level segmentation masks.

Multimodal biomedical framework aligning frozen single-cell and protein model encoders to an LLM's embedding space for zero-shot reasoning.

Scientific multitask language model whose byte-level genome modeling beats Evo 7B on DNA perplexity and mutation-effect prediction at 1.5B params.