Sold by: Anyscale
Deployed on AWS
Anyscale-creators of Ray-delivers an AI-native compute platform that accelerates development and enables scalable deployment of any AI workload. The platform provides a unified runtime that can distribute any Python code or AI library, including XGBoost, PyTorch, and vLLM, making it seamless to scale data processing, training or inference from a single machine to thousands of CPUs, GPUs, or both.
4.5
Overview
Anyscale provides teams with an AI-native compute platform, one that is Python-based, multimodal-ready and GPU optimized. Powered by Ray, the leading framework for scalable AI processing, Anyscale enables teams to build and deploy AI without limits.
Anyscale gives AI teams a production-ready platform that accelerates time to value, reduces TCO, and de-risks operating an internal AI development and deployment platform that supports both traditional machine learning and modern AI workloads.
Teams can get started quickly with our fully managed, Anyscale-hosted experience-or deploy into the customer VPC (virtual private cloud) via BYOC (bring your own cloud), with the flexibility to run on VM-based infrastructure (EC2) or Kubernetes environments (AWS EKS and SageMaker HyperPod).
Highlights
- Developer velocity: Develop on a multi-node backed IDE and seamlessly transition from dev to prod with self-service clusters for batch and online processing, without any cluster management.
- Enterprise-grade security: Anyscale runs directly inside your VM-based infrastructure (EC2) or Kubernetes environments (AWS EKS and SageMaker HyperPod), ensuring data and processing stays in your private cloud. It also integrates natively with AWS security frameworks, including AWS Identity and Access Management (IAM), inheriting your existing access controls, policies, and governance standards.
- Resilient and cost-efficient infrastructure: Ensure AI workloads stay reliable with built-in head node resilience, intelligent autoscaling, and safe rollouts. Advanced scheduling and GPU sharing maximize utilization and help prevent runaway costs as teams scale.
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If qualified, an express private offer gets you custom pricing and terms. Finalize your purchase in the AWS Marketplace console.
Details
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Delivery method
Deployed on AWS
Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Anyscale Contract | Aggregate of all Anyscale contract usage in U.S. Dollars e.g. Platform usage, Support, Advisory, Training, etc. | $1,000.00 |
Platform + Support (Express Private Offer) | Aggregate of Anyscale contract usage (Platform Usage and Support) in U.S. Dollars. Each unit purchased is $1,000 USD. Additionally, $1,000 USD of the monthly purchase will be applied towards the purchase of Developer Support as described here: https://www.anyscale.com/support. | $1,000.00 |
Platform + Support (Express PO) | Aggregate of Anyscale contract usage (Platform Usage and Support) in U.S. Dollars. Each unit purchased is $1,000 USD. Additionally, $1,000 USD of the monthly purchase will be applied towards the purchase of Developer Support as described here: https://www.anyscale.com/support. | $1,000.00 |
Dimension | Cost/unit |
|---|---|
Aggregate of all Anyscale contract usage in U.S. Dollars | $0.01 |
Dimensions summary
You buy this platform through a contract measured in U.S. dollars of aggregate usage. Two dimensions track total contract spend across everything you consume, such as platform usage, support, advisory, and training. Two other dimensions bundle Platform Usage and Support through an Express Private Offer, where each unit purchased equals $1,000. In those two dimensions, $1,000 of the monthly purchase goes toward Developer Support. All dimensions bill by dollar amount, so your cost scales directly with how much you use rather than by fixed tiers or instance sizes.
Top-of-mind questions for buyers
Each unit you purchase equals $1,000 in aggregate Anyscale contract usage. This covers Platform Usage and Support. Of the $1,000 monthly purchase, $1,000 goes toward Developer Support. So each unit maps to a fixed dollar block of combined platform and support spend.
The Anyscale Contract dimension tracks your total contract usage in U.S. dollars. This can include platform usage, support, advisory, and training. You draw down against your committed dollar amount as you consume these services, rather than paying separate line items per category.
Developer Support provides email support, documentation access, a status page, and community forum access. You submit issues via the Anyscale Console. Support hours run 6 AM to 6 PM Pacific time on business days. This portion is funded by $1,000 of each monthly purchase.
anyscale.com
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Vendor refund policy
All fees are non-refundable and non-cancellable except as required by law.
Custom pricing options
Request a private offer to receive a custom quote.
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Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Support offerings are listed at http://anyscale.com/support . Unless you contract for support via a Private Offer, your support is limited to public forums and documentation
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By Anyscale
By Lightning AI
By Domino Data Lab
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Distributed Computing Runtime
Unified runtime that distributes Python code and AI libraries across thousands of CPUs, GPUs, or both, scaling from single machine to large clusters
Multi-Framework Support
Support for distributed execution of XGBoost, PyTorch, vLLM, and other AI libraries within a single platform
Infrastructure Deployment Flexibility
Deployment options including fully managed Anyscale-hosted experience, bring-your-own-cloud (BYOC) into customer VPC, VM-based infrastructure (EC2), and Kubernetes environments (AWS EKS and SageMaker HyperPod)
Enterprise Security Integration
Native integration with AWS security frameworks including AWS Identity and Access Management (IAM) with inherited access controls, policies, and governance standards
Workload Optimization and Resilience
Built-in head node resilience, intelligent autoscaling, advanced scheduling, GPU sharing capabilities, and safe rollout mechanisms to maximize resource utilization and prevent cost overruns
Multi-Node Distributed Training
Supports multi-node training capabilities enabling scalable AI model training across multiple machines with on-demand compute resources including A100 and H100 GPUs.
Integrated Development Environment
Provides unified platform integrating data preparation, model development, distributed training, and application deployment within a single cohesive interface.
Pre-built Model Templates
Includes pre-built studios from expert contributors and PyTorch ecosystem optimized for state-of-the-art AI applications including LLMs, Diffusion models, and Graph Neural Networks.
Enterprise Security and Isolation
Offers enterprise-grade security features including Bring Your Own Cloud (BYOC) capability, fine-grained access control, and private networking to ensure data remains within customer accounts.
Serverless Deployment
Supports serverless deployment options enabling application deployment without infrastructure management overhead.
Self-Service Infrastructure Access
One-click, governed access to data, tools, and compute resources through a self-service portal with support for open-source tools including Jupyter, RStudio, SAS, Anaconda, MATLAB, and distributed compute frameworks like Spark, Ray, Dask, and MPI.
Centralized Knowledge Management
Central hub for AI operations and knowledge across the enterprise enabling reproducibility, reusability, and cross-functional collaboration with audit-ready platform capabilities.
Integrated MLOps Workflows
End-to-end model development, deployment, and monitoring capabilities within a unified platform with support for preferred tools and languages, including seamless integration with Amazon SageMaker.
Multi-Cloud and Hybrid Deployment
Support for deployment across public cloud, hybrid, and multi-cloud environments through Domino Nexus, enabling workload execution across any compute cluster in any cloud, region, or on-premises infrastructure.
Model Governance and Compliance
Turnkey model governance, monitoring, and remediation with robust controls for compliance, reproducibility tracking, and audit-ready processes designed for regulatory requirements including GxP processes.
Standard contract
No
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Customer reviews
Diwakar K.
Effortless Staffing Automation, Needs Better Guides
Reviewed on Aug 19, 2026
Review provided by G2
What do you like best about the product?
I like that Anyscale automates our US staffing tasks using AI, which helps quickly review large amounts of resume data. It makes our hiring process faster and easier by automatically organizing candidate details and matching the right people to jobs, so we can focus on finding the best talent quickly. The tool manages big workloads easily, is simple to use, speeds up data processing, and scales up when needed. It integrates well with existing tools like Python, Slack, AWS, and Github, which is great because it doesn't require learning new systems. Its flexibility allows it to fit our busy times, and it's safe and saves a lot of time by doing boring work for us. The initial setup was quite easy and straightforward.
What do you dislike about the product?
The system is too hard to learn and set up. Advanced features take too much time to figure out for our specific workflows. We need better guides and real examples. We also need simpler tools to check and manage our workloads so we can fix problems faster.
What problems is the product solving and how is that benefiting you?
Anyscale automates our staffing tasks, speeding up data processing and matching candidates efficiently. It handles repetitive tasks, allowing our team to focus on selecting top talent, but setting it up and learning advanced features can be challenging. I wish for better guides and simpler management tools.
Vineet B.
Powerful Open-Source Ray That Performs in Production
Reviewed on Aug 18, 2026
Review provided by G2
What do you like best about the product?
Powerful open-source software (Ray) that works well in production. The engineering team is smart and clearly knows what they’re doing.
What do you dislike about the product?
Startup life isn’t for everyone. The pace can be challenging for some.
What problems is the product solving and how is that benefiting you?
It eliminates the heavy DevOps burden of manually setting up, scaling, and managing multi-node CPU/GPU clusters.
ramanath j.
More Time Coding, Less Time Managing Distributed Infrastructure
Reviewed on Aug 13, 2026
Review provided by G2
What do you like best about the product?
You spend more time on the code/workflow and less on the plumbing of provisioning/maintaining distributed resources.
What do you dislike about the product?
ven with managed infrastructure, you still need to think about cluster sizing, concurrency, autoscaling behavior, failure handling, and workload/resource patterns.
What problems is the product solving and how is that benefiting you?
Anyscale is primarily solving the “how do we run Ray reliably at scale?” problem—especially when moving from experimentation to production workloads.
Shubh K.
Made It Easy to Build a Cloud storage for Clara AI data
Reviewed on Aug 13, 2026
Review provided by G2
What do you like best about the product?
It helped me create a sandbox for my product, Clara AI, so I could offer it to prospects after the product call.
What do you dislike about the product?
As of now everything is working perfectly smooth and cloud storage for Procol's product is a big plus
What problems is the product solving and how is that benefiting you?
My business requires heavy cloud requirements which is solved by Anyscale
Nikhil P.
Anyscale Makes Scaling Ray Workloads Smooth and Developer-Friendly
Reviewed on Aug 13, 2026
Review provided by G2
What do you like best about the product?
What I like most about Anyscale is how much it simplifies scaling AI workloads. The platform feels flexible and developer-friendly for running distributed workloads, and it reduces the operational burden that comes with managing infrastructure. I also appreciate its strong integration with the Ray ecosystem, along with the way it lets me move smoothly from experimentation to production without a lot of friction.
What do you dislike about the product?
One drawback of Anyscale is that it can take some time to get familiar with the platform and its configuration options. For teams that are new to distributed computing or Ray, the learning curve can feel a bit steep, and certain workflows could be made more intuitive and straightforward.
What problems is the product solving and how is that benefiting you?
Anyscale helps address the complexity of building and scaling distributed AI workloads. It makes it easier for us to move from experimentation to production without having to manage as much infrastructure ourselves. As a result, we save engineering time, deployment and scaling are simpler, and we can focus more on improving our models and applications instead of spending effort on infrastructure management.