Medicine2026
Hugging Face (HuggingFaceBio) · USA
An open 14.8B language model for working with DNA, built on Qwen3-14B. You send a raw sequence right in an ordinary chat, and it answers in English: it judges whether a mutation is benign or pathogenic, finds regions that control gene activity, assigns a sequence to an organism group, predicts the next bases and explains its reasoning. DNA and text go in one stream, with DNA encoded in groups of six bases. By the authors' tests, on five sets it scores 66.7% without reasoning, 27 points above Qwen3-14B, and costs about 1,800 times less than GPT-6.1 Sol at a close result. It fits on a single 80 GB card, so sensitive data can stay with you. Viral data was excluded from training because of the risks. The conclusions are computed and do not replace laboratory verification.
- assessing DNA variants: benign or pathogenic
- finding regions that control gene activity
- a research assistant for biologists on your own server
- Sizes
- 14.8B
- Hardware
- from: 1 GPU
Medicine2026
NVIDIA · USA
A language model for computed tomography: looks at a whole chest or abdominal CT volume, not separate slices, writes structured reports and answers questions with reasoning. English only.
- a draft CT report for a physician
- yes-or-no answers about a scan with reasoning
- research in medical imaging
- Sizes
- 4B (based on Qwen3.5-4B with a 3D encoder)
- Hardware
- from: 1 GPU
Medicine2026
MIT CSAIL, Massachusetts General Hospital and Harvard Medical School · USA
Finds 60 anatomical structures on an X-ray: ribs, vertebrae, pelvis and limb bones. They can be used to measure, for example, the curvature angle of the spine automatically. It does not look for pathologies and does not tell right from left.
- labeling anatomy on X-ray images
- measuring the spine curvature angle
- matching fluoroscopy frames with CT for navigation
- Sizes
- a small U-Net, 256 by 256 pixel images
- Hardware
- from: Laptop
MedicineGGUF2023–2026
FreedomIntelligence (The Chinese University of Hong Kong, Shenzhen) · China
A large family of medical models: chat, an imaging version, the reasoning HuatuoGPT-o1 and the new HuatuoGPT-3 on Qwen3. Does not replace a doctor; decisions are made by a specialist.
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Hints for doctors when reviewing images (Vision)
- Sizes
- 7B – 72B
- Hardware
- from: Laptop
Biology and chemistry2022–2026
AlQuraishi Lab (Columbia University) and the OpenFold consortium · USA
A fully open reproduction of AlphaFold 2 and then AlphaFold 3 under Apache 2.0, with training data. OpenFold3 predicts complexes of proteins, nucleic acids and ligands.
- Predicting structures of proteins and ligand complexes
- Fine-tuning on the company's own data (training code is open)
- An in-house structural analysis service without sending data outside
- Sizes
- a single set of weights per version
- Hardware
- from: 1 GPU
Biology and chemistry2022–2026
EvolutionaryScale / Chan Zuckerberg Biohub (ESM-2 — Meta AI) · USA
Protein language models: they understand amino acid sequences, predict structure (ESMFold2) and help with protein design. Since 2026 all open versions are under MIT.
- Protein embeddings for predicting properties (stability, solubility)
- Predicting 3D structures of proteins and complexes
- Screening enzyme and antibody design candidates before lab work
- Sizes
- 8M – 15B (ESM-2), 300M – 6B (ESM C), 1.4B (open ESM3)
- Hardware
- from: Laptop
MedicineOllama2023–2026
EPFL · Switzerland
Open medical models from Swiss EPFL, fine-tuned on clinical guidelines on top of various base models. Does not replace a doctor; decisions are made by a specialist.
- Answering staff questions based on clinical guidelines
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Sizes
- 2B – 70B
- Hardware
- from: Laptop
Computer vision2024–2026
Meta · USA
Meta's models for analyzing people in photos: pose keypoints, body part segmentation, normals and depth. Sapiens2 was trained at high resolution and adds human matting.
- Pose and body keypoint detection
- Segmentation of body parts and clothing
- Separating a person from the background
- Sizes
- 0.1B – 5B
- Hardware
- from: Laptop
Search and RAGGGUF2025–2026
Octen · USA / Singapore
Qwen3-Embedding models fine-tuned by the startup Octen for search in legal, financial and medical texts. As of January 2026 the 8B version topped the RTEB leaderboard.
- Search across contracts and case law
- Search across financial reports
- Search across long documents up to 32K tokens
- Sizes
- 0.6B – 8B
- Hardware
- from: Laptop
MedicineGGUF2025–2026
Zhejiang University · China
A medical model for text, images, 3D scans and video: from a light 4B to a large MoE. Does not replace a doctor; decisions are made by a specialist.
- Hints for doctors when reviewing images and CT scans
- Draft reports and discharge summaries
- Searching medical literature
- Sizes
- 4B – 235B-A22B
- Hardware
- from: Laptop
Biology and chemistry2024–2026
Arc Institute (with Together AI, Stanford, NVIDIA) · USA
DNA language models with context up to a million nucleotides: they assess the impact of mutations, annotate genomes and generate sequences. Evo 2 is trained on genomes from all domains of life.
- Assessing the likely harmfulness of genetic variants for research
- Annotating genomes of microorganisms and plants
- Finding promising sequences in breeding and synthetic biology
- Sizes
- 1B – 40B
- Hardware
- from: 1 GPU
MedicineGGUF2025–2026
Ant Healthcare (Ant Group) and Zhejiang Provincial Medical Information Center · China
A large medical MoE model based on Ling-flash-2.0: 100B parameters with 6B active, so it answers quickly. Does not replace a doctor; decisions are made by a specialist.
- Reference answers to staff on clinical questions
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Sizes
- 100B-A6B
- Hardware
- from: 1 GPU
TextGGUF2023–2026
Baichuan Intelligence · China
First general-purpose Chinese models, then a medical line from 2025. Baichuan-M3 (based on Qwen3-235B) is trained to model a doctor's clinical reasoning.
- Reference assistant for doctors
- Preliminary patient intake questions
- Analysis of medical documents
- Sizes
- 7B – 235B-A22B
- Hardware
- from: Laptop
Medicine2023–2026
Stanford AIMI · USA
Stanford models for chest X-rays: they describe the image and prepare a draft report. Does not replace a doctor; decisions are made by a specialist.
- A draft X-ray description for the radiologist
- Hints for doctors when reviewing images
- Checking reports for completeness
- Sizes
- 3B – 8B
- Hardware
- from: Laptop
MedicineGGUF2025–2026
Alibaba DAMO Academy · China
Alibaba's medical model based on Qwen2.5-VL: understands many types of medical images and medical text, and can reason step by step. Does not replace a doctor; decisions are made by a specialist.
- Hints for doctors when reviewing images
- Draft reports and discharge summaries
- Searching medical literature
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
MedicineOllama2025–2026
Google · USA
Google's medical version of Gemma: reads medical texts and images (X-ray, dermatology, histology). A tool for doctors and developers; does not replace a doctor, decisions are made by a specialist.
- Draft discharge summaries and reports for a doctor to review
- Hints for doctors when reviewing images
- Searching and summarising medical literature
- Sizes
- 4B – 27B
- Hardware
- from: Laptop
Biology and chemistry2024–2025
MIT (Jameel Clinic) and Recursion · USA
An open MIT-licensed alternative to AlphaFold 3: predicts structures of protein, DNA and small-molecule complexes; Boltz-2 estimates binding strength, BoltzGen designs new binding proteins.
- Predicting how a candidate molecule binds to a target protein
- Ranking compounds by predicted binding strength before synthesis
- Designing binder proteins for a given target
- Sizes
- checkpoints of about 2 GB
- Hardware
- from: 1 GPU
Computer vision2023–2025
Meta · USA
Foundation models that turn an image into a numeric "fingerprint". They are used to build similar-image search, classification and segmentation without large labeled datasets.
- Finding similar products and photos
- Image classification on small datasets
- Base for your own quality-control models
- Sizes
- 21M – 7B
- Hardware
- from: Laptop
MedicineGGUF2025
Intelligent Internet · UK
Reasoning medical models on Qwen3, designed to run on an ordinary computer. Does not replace a doctor; decisions are made by a specialist.
- Reference answers to staff with the reasoning shown
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Sizes
- 7B – 32B
- Hardware
- from: Laptop
Medicine2025
Google · USA
Google's lightweight encoder for medical images and text, the same one inside MedGemma. Sorts images and finds similar ones. Does not replace a doctor; decisions are made by a specialist.
- Finding similar images in a clinic's archive
- Pre-sorting images for a doctor
- A base for your own image classifiers
- Sizes
- about 0.9B
- Hardware
- from: Laptop
Acoustic monitoring2024–2025
Google · USA
A model for health sounds: coughing, breathing, throat clearing. It provides features on top of which a researcher builds their own model and draws no conclusions about illness itself. It does not replace a doctor; decisions are made by a specialist. Voice recordings are personal data, so check the procedure with a lawyer.
- Features of cough and breathing sounds for your own model
- Research projects in health acoustics
- Selecting cough and breathing fragments from a recording
- Sizes
- a ViT-Large class model, trained on more than 300 million two-second clips
- Hardware
- from: Laptop
Medicine2024–2025
Bioptimus · France
Pathology foundation models from France's Bioptimus with 1.1B parameters, plus the compact H0-mini. The first version is open under Apache 2.0. Does not replace a doctor; decisions are made by a specialist.
- Histology slide patch features for research models
- A prototype for sorting slides by tissue type
- Research projects linking morphology and molecular data
- Sizes
- 86M (H0-mini) – 1,1B
- Hardware
- from: Laptop
Medicine2024–2025
Mahmood Lab (Mass General Brigham, Harvard) · USA
A foundation model for histology slides: turns patches of digital slides into features for tissue classification. Does not replace a doctor; decisions are made by a specialist.
- Research classifiers of tissue types from digital slides
- Finding similar cases in a slide archive
- Preparing features for research prognosis models
- Sizes
- about 300M (UNI) – about 680M (UNI2-h)
- Hardware
- from: Laptop
Computer vision2022–2025
University of Sydney and JD Explore Academy · Australia / China
A simple, accurate model for human pose estimation via keypoints. ViTPose++ handles human, animal and whole-body poses; built into the Transformers library.
- Body keypoints in photos and video
- Motion analysis in sports and rehabilitation
- Monitoring work postures and safety practices
- Sizes
- 33M – about 1B
- Hardware
- from: Laptop
Medicine2024
Mahmood Lab (Mass General Brigham, Harvard) · USA
Image-plus-text models for pathology: search slides by an English description, classify without fine-tuning; TITAN describes a whole slide. Does not replace a doctor; decisions are made by a specialist.
- Text-query search across a slide archive for research
- Draft slide descriptions for research projects
- Tissue classification without labels at the start of a study
- Sizes
- about 160M – 300M
- Hardware
- from: Laptop
Biology and chemistry2024
Google DeepMind and Isomorphic Labs · UK
The reference model for the structure of biomolecules and their complexes. Weights are provided for non-commercial research only; companies need commercial access via Google Cloud or open alternatives (Boltz, OpenFold3).
- Academic research on protein and complex structures
- Benchmarking open alternatives against the reference on your own targets
- Sizes
- a single set of weights
- Hardware
- from: 1 GPU
Moderation and safety2024
iiiorg · not disclosed
A popular detector of 17 types of personal data in six European languages. No Russian and a non-commercial license: suitable for trials and research.
- Finding personal data in texts
- Comparing the quality of PII detectors
- Sizes
- 278M
- Hardware
- from: Laptop
MedicineNot maintained2024
Paige · USA
Paige's pathology foundation model, trained on millions of digital slides. The first version is Apache 2.0, the second is for research only. Does not replace a doctor; decisions are made by a specialist.
- Slide patch features for research classifiers
- Selecting slides for re-review in research projects
- Comparison with other pathology models on your own archive
- Sizes
- about 632M
- Hardware
- from: Laptop
MedicineGGUFNot maintained2023–2024
M42 Health · UAE
Clinical models from Abu Dhabi-based M42, built on Llama and tuned to answer medical questions. Does not replace a doctor; decisions are made by a specialist.
- Reference answers to staff on clinical questions
- Draft discharge summaries and letters for a doctor to review
- Searching medical literature
- Sizes
- 8B – 70B
- Hardware
- from: Laptop
MedicineGGUFNot maintained2024
Avignon University and Nantes University · France
Mistral 7B fine-tuned on PubMed Central papers, plus several merges with the general model. Compact and easy to run. Does not replace a doctor; decisions are made by a specialist.
- Searching and summarising medical papers
- Draft reference materials for staff
- Explaining medical terminology
- Sizes
- 7B
- Hardware
- from: Laptop
MedicineGGUFNot maintained2024
Saama AI Research · India
Llama 3 fine-tuned on medical and biological data. One of the first strong open medical models of 2024. Does not replace a doctor; decisions are made by a specialist.
- Extracting data from medical documents
- Draft discharge summaries for a doctor to review
- Searching medical literature
- Sizes
- 8B, 70B
- Hardware
- from: Laptop
MedicineNot maintained2023
Bo Wang's lab (University of Toronto, Vector Institute) · Canada
An early medical model on Llama 2 70B, trained on dialogues based on medical texts. Now mainly of research interest. Does not replace a doctor; decisions are made by a specialist.
- Research pilots on medical dialogue
- Training materials for staff
- Comparison with newer medical models
- Sizes
- 70B
- Hardware
- from: 1 GPU
MedicineNot maintained2023
Shanghai Jiao Tong University and Shanghai AI Lab · China
An early general-purpose radiology model: understands 2D and 3D images (CT, MRI) together with text. More of a research base. Does not replace a doctor; decisions are made by a specialist.
- Research pilots on CT and MRI analysis
- Hints for doctors when reviewing images
- A base for fine-tuning on the clinic's own images
- Sizes
- size not stated on the model card
- Hardware
- from: 1 GPU
