Ray

Ray

Anyscale
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About

Develop on your laptop and then scale the same Python code elastically across hundreds of nodes or GPUs on any cloud, with no changes. Ray translates existing Python concepts to the distributed setting, allowing any serial application to be easily parallelized with minimal code changes. Easily scale compute-heavy machine learning workloads like deep learning, model serving, and hyperparameter tuning with a strong ecosystem of distributed libraries. Scale existing workloads (for eg. Pytorch) on Ray with minimal effort by tapping into integrations. Native Ray libraries, such as Ray Tune and Ray Serve, lower the effort to scale the most compute-intensive machine learning workloads, such as hyperparameter tuning, training deep learning models, and reinforcement learning. For example, get started with distributed hyperparameter tuning in just 10 lines of code. Creating distributed apps is hard. Ray handles all aspects of distributed execution.

About

RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

ML and AI Engineers, Software Developers

Audience

RunPod is designed for AI developers, data scientists, and organizations looking for a scalable, flexible, and cost-effective solution to run machine learning models, offering on-demand GPU resources with minimal setup time

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

$0.40 per hour
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 5.0 / 5
design 5.0 / 5
support 5.0 / 5

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Anyscale
Founded: 2019
United States
ray.io

Company Information

RunPod
Founded: 2022
United States
www.runpod.io

Alternatives

Alternatives

Vertex AI

Vertex AI

Google
AWS Neuron

AWS Neuron

Amazon Web Services
Vertex AI

Vertex AI

Google

Categories

Categories

Integrations

Amazon Web Services (AWS)
Google Cloud Platform
PyTorch
TensorFlow
Amazon EC2 Trn2 Instances
Anyscale
Axolotl
Dask
Databricks Data Intelligence Platform
DeepSeek Coder
Google Drive
Google Kubernetes Engine (GKE)
Hermes 3
Kubernetes
Llama 3.1
Llama 3.2
Microsoft Azure
Phi-4
TinyLlama
io.net

Integrations

Amazon Web Services (AWS)
Google Cloud Platform
PyTorch
TensorFlow
Amazon EC2 Trn2 Instances
Anyscale
Axolotl
Dask
Databricks Data Intelligence Platform
DeepSeek Coder
Google Drive
Google Kubernetes Engine (GKE)
Hermes 3
Kubernetes
Llama 3.1
Llama 3.2
Microsoft Azure
Phi-4
TinyLlama
io.net
Claim Ray and update features and information
Claim Ray and update features and information