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.
4.2
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.
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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.
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Request a private offer to receive a custom quote.
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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
No
Customer reviews
reviewer2788458
Fraud prevention has improved and security strengthens while monitoring and CI workflows still need work
Reviewed on Dec 16, 2025
Review from a verified AWS customer
What is our primary use case?
In my field, which is a FinTech company, Anyscale Platform is mainly used for security purposes, protecting data and everything by applying all the basic features from the platform.
For us, we are mainly using Anyscale Platform with VS Code development for providing services for production deployment from my end, as per my role.
We mainly do coding with Anyscale Platform, but if you dig deeper, as I mentioned, we are a FinTech company, so we work daily to prevent fraud. The entire integration with the platform helps us address this, along with faster service provision and risk assessment using Anyscale services.
What is most valuable?
Anyscale Platform provides top features including AI and ML workflows which are reliable and scalable, along with management capabilities. The integration with services like AWS and GCP is beneficial, and we also have a built-in monitor.
The monitoring feature of Anyscale Platform, particularly the metrics dashboard, stands out because it shows GPU memory usage and visualizations that simplify our experience with the entire dashboard along with a well-prepared debugging and logging system.
Since adopting Anyscale Platform, we have observed a drastic improvement in overall security, and it is cost-efficient. The performance and productivity boost have led to a reduction in the number of people needed for operations, and scalability has also improved significantly.
What needs improvement?
Anyscale Platform sometimes lags and there is no response, which happens rarely but is noted. Additionally, a built-in CI/CD integration could be a useful addition.
That was just a suggestion from my end regarding CI/CD integration since we have been using it differently, but I cannot add more than that.
The overall performance and boost from Anyscale Platform is amazing, but I still see some improvement points, which is why I chose that score.
For how long have I used the solution?
I have been using Anyscale Platform for more than over a year.
What do I think about the stability of the solution?
Anyscale Platform is stable.
What do I think about the scalability of the solution?
The scalability of Anyscale Platform is good.
How are customer service and support?
Customer support is outstanding, as the support team is always available whenever we need to reach out or raise a ticket, and they assist us effectively.
I rate the customer support a ten out of ten.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I did not previously use a different solution.
How was the initial setup?
The entire process with pricing, setup cost, and licensing was smooth, with the costing sheet metrics provided and approval received, which seemed reasonable.
What was our ROI?
I do not really receive reports on exact numbers or budget saved, but if four people used to work on a particular task, that has reduced to one due to Anyscale Platform, allowing others to focus on different tasks.
I mentioned previously that we reduced the number of people needed for certain tasks from four to one, which signifies fewer people, less money saved, and time saved, although I do not have the entire metrics available.
What's my experience with pricing, setup cost, and licensing?
The entire process with pricing, setup cost, and licensing was smooth, with the costing sheet metrics provided and approval received, which seemed reasonable.
Which other solutions did I evaluate?
The other options were evaluated, but Anyscale Platform seemed the best choice.
What other advice do I have?
I advise others looking into using Anyscale Platform to consider its scalability and the services provided, which are all on point. I provided a review rating of seven out of ten.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Rakshit A.
Great tool for scaling AI workloads
Reviewed on Nov 19, 2025
Review provided by G2
What do you like best about the product?
What impresses me most is how it handles the heavy lifting for Ray. I can develop my AI application code right on my laptop and then deploy it to a large cluster without having to rewrite anything or wrestle with complex infrastructure setups. This effectively bridges the gap between code that only "works on my machine" and a real production environment, which is particularly useful when scaling LLM workloads and managing distributed training. In the end, it saves me a considerable amount of time on DevOps tasks.
What do you dislike about the product?
The pricing structure can feel somewhat unclear, making it difficult at times to anticipate your final monthly bill. This is especially noticeable when compared to the more straightforward cost management you get with handling raw EC2 instances on your own.
What problems is the product solving and how is that benefiting you?
I use Anyscale mainly to overcome the infrastructure challenges of scaling Python machine learning code from my local laptop to a large distributed cluster. My team operates a substantial Retrieval-Augmented Generation (RAG) pipeline, which includes OCR processing and embedding generation for millions of PDF files. Previously, running this workload on a single large EC2 instance would take weeks, and managing AWS Batch jobs involved a lot of boilerplate and ongoing DevOps work. With Anyscale, we were able to wrap our existing Python functions with Ray decorators, enabling the platform to automatically spin up a cluster of over 50 spot instances, process 2TB of data in less than four hours, and then scale back down to zero. This approach has reduced our compute costs by about 60% by taking advantage of spot instances without the need for manual fault-tolerance solutions, and it has allowed my data scientists to independently run large-scale experiments without waiting for DevOps to provision resources.
Mohammad hanif A.
AI/ML
Reviewed on Sep 11, 2025
Review provided by G2
What do you like best about the product?
Anyscale makes it easy to scale AI/ML workloads without worrying about infrastructure complexity
What do you dislike about the product?
Documentation could be more beginner-friendly with clearer end-to-end examples
What problems is the product solving and how is that benefiting you?
solves the challenge of scaling machine learning and AI workloads without requiring deep expertise in distributed systems. eg remove complexity
Subrat M.
Scalable and reliable platform for AI workloads
Reviewed on Aug 25, 2025
Review provided by G2
What do you like best about the product?
Anyscale simplifies the process of moving AI and ML workloads from development to production. Since it is built on Ray, it enables scalability without requiring major code changes.
What do you dislike about the product?
The platform has a noticeable learning curve, particularly for teams unfamiliar with Ray concepts. Pricing is not always transparent, which makes cost planning more challenging.
What problems is the product solving and how is that benefiting you?
Anyscale addresses the challenge of running distributed ML and GenAI workloads efficiently.
Akanksha R.
Good
Reviewed on Aug 19, 2025
Review provided by G2
What do you like best about the product?
The Anyscale platform was essential as it fully managed, production-ready version of Ray, offering a simplified and integrated developer experience and it made easy to build and it has good scalability.
What do you dislike about the product?
About the disadvantage is during building there is little trouble when debugging trouble.
What problems is the product solving and how is that benefiting you?
I solved the scalability and robustness problems as it was easier to solve.