10 alternatives to monai.io, matched by what they do.
| Rank | Tool & Tagline | Official Domain | Monthly Visits | MoM Growth | Pricing Model | Primary Market | Rating | Compare |
|---|
| ● | monai.io | monai.io | 9.65K | -2.22K (-18.7%) | Free | United States | — | Profile |
| 1 | Corti | corti.ai | 24.97K | -288 (-1.1%) | Contact for Pricing | United States | 4.4 | Compare |
| 2 | Binah.ai | binah.ai | 6.44K | -2.31K (-26.4%) | Contact for Pricing | United States | 4.3 | Compare |
| 3 | Meta Segment Anything Model 2 (SAM 2) | ai.meta.com | 5.36M | 1.69M (+46.1%) | Free | United States | 4.8 | Compare |
| 4 | Roboflow | roboflow.com | 1.43M | 88.17K (+6.6%) | Freemium, Contact for Pricing | United States | 4.6 | Compare |
| 5 | Ultralytics | ultralytics.com | 793.42K | 63.49K (+8.7%) | Freemium | China | 4.6 | Compare |
| 6 | Captum | captum.ai | 4.46K | -3.33K (-42.7%) | Free | United States | 4.7 | Compare |
| 7 | MindSpore (昇思) | mindspore.cn | 46.57K | -24.12K (-34.1%) | Free | Singapore | 4.5 | Compare |
| 8 | Replicate AI | replicate.com | 904.04K | -82.59K (-8.4%) | Paid | United States | 4.6 | Compare |
| 9 | Together AI | together.ai | 1.65M | 647.75K (+64.9%) | Freemium, Paid | United States | 4.7 | Compare |
| 10 | DeepInfra | deepinfra.com | 457.81K | -44.51K (-8.9%) | Paid | United States | 4.6 | Compare |
SpecialistProvides clinical-grade AI and medical speech workflows, but focuses on clinical practice rather than PyTorch medical image research.
SpecialistProvides clinical-grade AI and medical speech workflows, but focuses on clinical practice rather than PyTorch medical image research.
SpecialistSpecializes in health data and vital sign measurements from video, whereas MONAI offers general medical imaging deep learning tools.
SpecialistSpecializes in health data and vital sign measurements from video, whereas MONAI offers general medical imaging deep learning tools.
Free / Open-sourceOffers foundational open-source image segmentation for object tracking, but lacks MONAI's specialized medical imaging and DICOM workflow integrations.
Free / Open-sourceOffers foundational open-source image segmentation for object tracking, but lacks MONAI's specialized medical imaging and DICOM workflow integrations.
Free / Open-sourceStreamlines computer vision model building and deployment, but lacks MONAI's specific healthcare and 3D medical imaging architecture.
Free / Open-sourceStreamlines computer vision model building and deployment, but lacks MONAI's specific healthcare and 3D medical imaging architecture.
SpecialistDelivers real-time computer vision and object detection models, but is not tailored for medical imaging and volumetric scans.
SpecialistDelivers real-time computer vision and object detection models, but is not tailored for medical imaging and volumetric scans.
Free / Open-sourceProvides PyTorch model interpretability and attribution algorithms, but focuses on model explanation rather than end-to-end medical workflows.
Free / Open-sourceProvides PyTorch model interpretability and attribution algorithms, but focuses on model explanation rather than end-to-end medical workflows.
Free / Open-sourceActs as an open-source deep learning framework for training and deployment, but uses a different ecosystem than PyTorch.
Free / Open-sourceActs as an open-source deep learning framework for training and deployment, but uses a different ecosystem than PyTorch.
Provides cloud infrastructure for running and deploying machine learning models, but lacks pre-built medical imaging tools.
Provides cloud infrastructure for running and deploying machine learning models, but lacks pre-built medical imaging tools.
Free / Open-sourceTogether AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
Free / Open-sourceTogether AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.
