Anyscale

Managed Ray platform for distributed training, batch inference and data processing on GPU clusters.

Infrastructure by Anyscale

IndexedApache-2.0★ 44,115

Install

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pip install ray

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About

Anyscale runs Ray-based distributed workloads such as multimodal data curation, distributed model training, batch embedding generation and post-training. The platform is powered by Ray, which the page describes as a widely adopted AI compute engine.

Use cases: model-inference, data-pipelines

Reviews

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Fact sheet

Category: Inference · model serving
Self-host: Yesanyscale.com
Open source: Yesgithub.com

Plans

Pay as you go	Contact sales	usage-based, billed per instance-hour in Anyscale Credits, e.g. NVIDIA L4 0.9542 per hour
Committed contracts	Contact sales	volume discounts and reservations, talk to sales

From the vendor's pricing page, read Oct 24, 2026.

Facts read from the vendor's own pages by claude-haiku-5-5 on Oct 24, 2026; a fact is shown only with the page it came from.

Signals

Stars: 44,115
Forks: 8,193
Open issues: 2,832
Last commit: Oct 24, 2026 (4 days ago)
Last release: Oct 2, 2026 (26 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Packages: pypi ray
License: Apache-2.0
Repository: github.com/ray-project/ray
Website: www.anyscale.com
Docs: docs.anyscale.com
First seen: Oct 24, 2026
Last checked: Oct 24, 2026
Source: Website Pricing page README Docs github-graphql

Cite this page

Anyscale. Agent Mart. https://agentmart.dev/infrastructure/anyscale (last updated 2026-10-24)