Anyscale

What is Anyscale?

Anyscale is a fully managed platform for Ray, the open-source distributed computing framework, from the team behind it. It runs Ray clusters for you, scales them up and down automatically, and handles scheduled jobs and low-latency services in production. Teams use it to curate data, train models, run batch inference and serve models, and existing open-source Ray workloads can be migrated without code changes. You can deploy on Anyscale-hosted infrastructure, which is the quickest way to start, or bring your own cloud so work runs inside your own VPC, on Kubernetes or on-premises with 24x7 support. Built-in tooling includes Grafana dashboards, APIs and SDKs for CI/CD, and cost tracking by job, cluster and user. Pricing is usage-based with no fixed monthly fee: one Anyscale Credit equals $1, CPU-only compute starts at 0.0135 credits an hour, and an NVIDIA T4 GPU is 0.5682 credits an hour. Committed contracts unlock volume discounts.

Use cases

• Run distributed Python workloads with Ray
• Fine-tune and train models on GPU clusters
• Process multimodal data in batches
• Serve models with online inference
• Migrate open-source Ray to a managed service
• Track compute cost by job and user
• Use existing GPU reservations in your own cloud

Who it's for

• ML engineers
• Data engineers
• AI platform teams
• Foundation model builders

Why use Anyscale

• You skip operating Ray clusters yourself, which frees engineers to work on models and pipelines.
• Bring Your Own Cloud keeps data in your own VPC and lets you use GPU reservations you already hold.
• Usage-based billing has no monthly fixed fee, and discounts grow with volume.
• Existing Ray code moves over with no changes, so evaluation is low effort.
• Direct access to the engineers behind Ray is part of the support offering.

Anyscale features

• Fully managed Ray clusters with serverless autoscaling
• Hosted deployment on Anyscale infrastructure
• Bring Your Own Cloud on any cloud, Kubernetes or on-prem
• Production jobs on a schedule and low-latency services
• Out-of-the-box Grafana dashboards for jobs and resources
• APIs and SDKs for automation and CI/CD pipelines
• Cost tracking by jobs, clusters and users
• Instance catalog with AWS EC2 GPU and CPU types
• Marketplace invoicing through AWS, Azure or GCP for BYOC
• Support tiers from Developer to Platinum with severity-based response times

Anyscale integrations

• Ray
• Grafana
• AWS
• Azure

How to get started with Anyscale

1. Write your workload in Python with Ray, using Ray Data, Train or Serve as needed.
2. Choose Hosted for a fast start or Bring Your Own Cloud to deploy in your own account.
3. Submit jobs or deploy services, and Anyscale creates and scales the clusters.
4. Monitor health in Grafana dashboards and watch spend by job, cluster and user.
5. Move to a committed contract to get volume discounts as usage grows.

Anyscale limitations

• Hosted deployments are available in limited regions and run on VMs
• Hosted support is business hours only, with 5 case submissions
• Billing is usage-based, so costs vary with the instances you run
• Committed contract discounts are not priced on the page

Anyscale pricing

Anyscale has no free plan. Plans start at $0.01 usage-based, according to the official pricing page on 24 Oct 2026.

Anyscale plans

• Pay as you go

  From 0.0135 credits/hr

  1 Anyscale Credit = $1; CPU-only instance

  • Only pay for compute you use
  • No monthly fixed fees
  • Hosted or Bring Your Own Cloud

• Committed contracts

  Price on vendor site

  • Volume discounts
  • Use existing GPU reservations
  • Discounts scale with usage

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

Anyscale alternatives

The main Anyscale alternatives listed on Debuly are Databricks, Modal, Fireworks AI, Together AI, Baseten and Lambda. The table compares pricing and platforms; order is A–Z.

1. 

   Baseten

   Inference platform for deploying open-source, custom and fine-tuned AI models, with per-token Model APIs and dedicated GPUs.

   Developer platforms
   PaidVisit Baseten (official site)
2. Da

   Databricks

   Data and AI platform for data engineering, warehousing, governance, dashboards and AI agents, billed by usage on AWS, Azure and GCP.

   Developer platformsAutomation and agentsProductivity
   Free trialVisit Databricks (official site)
3. 

   Fireworks AI

   Inference and training platform for open models: pay-per-token serverless APIs, GPU deployments, fine-tuning and reserved capacity.

   Developer platformsCodingAutomation and agents
   PaidVisit Fireworks AI (official site)
4. 

   Lambda

   GPU cloud for AI with on-demand NVIDIA instances and reserved 1-Click Clusters for training, fine-tuning and inference.

   Developer platformsCoding
   PaidVisit Lambda (official site)
5. 

   Modal

   Serverless cloud platform for running AI inference, training, batch jobs and agent sandboxes, billed per second of compute.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Modal (official site)
6. 

   Together AI

   AI cloud for running open-source models through serverless and batch inference, dedicated endpoints, GPU clusters and fine-tuning.

   Developer platformsCoding
   PaidVisit Together AI (official site)

Anyscale FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from anyscale.com · fetched 23 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

Spot an error? Report an issue with this listing. We also remove a logo or image on the owner's request.