Anyscale | Production-Ready AI with Ray
Anyscale | Production-Ready AI with Ray 图标

Anyscale | Production-Ready AI with Ray

anyscale.com

Powered by Ray, Anyscale empowers AI builders to run and scale all ML and AI workloads on any cloud and on-prem.

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The Best Place to Build and Run AI with Ray

From the creators of Ray – Anyscale gives you a platform to run and scale all your ML and AI workloads, from data processing to training and inference.

Get Started with $100 Credit Book Demo

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  • notion-logo

  • runway-logo

  • pi wordmark

  • attentive-logo

  • canva-logo

  • coinbase-logo

  • handshake-logo

  • notion-logo

  • runway-logo

  • pi wordmark

  • attentive-logo

  • canva-logo

  • coinbase-logo

  • handshake-logo

  • notion-logo

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Announcing  First-Party Service on Azure Cloud

Announcing First-Party Service on Azure Cloud

We’re excited to announce a new AI-native compute service co-engineered with Microsoft delivered as a fully managed, first-party offering on Azure. Now in private preview.

Read the Blog

Ray is the Unified Compute Engine for the AI Era

Ray is an open-source framework that helps developers scale data processing, training, and inference workloads from laptops to tens or thousands of nodes.

  • Python-native. Distribute Python functions using familiar frameworks and data structures.
  • Multimodal. Process all data modalities, including images, video, text, audio, tabular datasets, and more.
  • Heterogeneous. Coordinate task execution across CPUs, GPUs, or other accelerators in a single cluster.

Learn Ray

Anyscale is the Best Platform for Ray

Ready from day one to help you build faster, scale easier, and operate with confidence.

Build. Debug. Deploy. Repeat.

DEVELOPER AGILITY

Build. Debug. Deploy. Repeat.

Interactive dev console with advanced workload observability to help you debug quickly, and seamlessly transition from dev to prod.

  • Built-in IDE. Cloud-based, scalable dev environments with idle termination to reduce costs accessible via VSCode, Jupyter, and Cursor.

  • Workload Observability. Debug faster with profiling tools built for distributed workloads.

  • Dependency Management. Auto propagate container and uv dependencies across Ray nodes.

Watch Demo

Deploy Anywhere. Scale Reliably.

PRODUCTION RESILIENCE

Deploy Anywhere. Scale Reliably.

Deploy fault-tolerant Ray clusters in your cloud of choice with built-in resilience, auto-scaling, and no manual ops.

  • Fault Tolerant. Heterogeneous (CPU/GPU) VM or K8s cluster deployments with proactive unhealthy node draining and replacement

  • Zero-downtime upgrades. Upgrade with confidence using built-in rollback and seamless transitions.

  • Monitoring & Alerting. Managed Prometheus and Grafana dashboards, backed by persistent logs.

Explore the Platform

Keep GPUs Busy – and Budgets Lean

COST EFFICIENCY

Keep GPUs Busy – and Budgets Lean

Boost performance with Anyscale optimizations. Efficiently manage jobs or users with built-in governance and cost controls.

  • Anyscale Runtime. Proprietary optimizations for every stage of the AI pipeline, from data preparation to training and inference.

  • Spot Instances. Reduce costs with reliable spot instance management, orchestration, and fall back to on-demand.

  • Cost Governance. Monitor usage across teams and keep costs in check with budgets and quotas.

Book a Demo

One Platform. Every AI Workload.

From data prep to inference — if it’s Python, it runs better with Ray on Anyscale.

RAGStable DiffusionBatch InferenceFine-tuningLLMsXGBoostDistributed TrainingVideo ProcessingGenerative AIData ProcessingParallel Processing

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Starting with Ray for distributed AI/ML \
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Explore Ray core AI libraries, such as Ray Data and Ray Train, and learn how to use them for large-scale training and batch inference with GenAI and LLMs.\
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30 mins | Beginner\
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Open
📝\
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LLM training and inference \
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Fine-tune an LLM to perform batch inference and online serving for entity recognition.\
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30 mins | Beginner\
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Open
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Audio batch inference \
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Use LLMs as judges to curate and filter audio datasets for quality and relevance.\
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30 mins | Advanced\
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Open
🌃🚀\
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Reinforcement Learning for LLMs with SkyRL \
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Reinforcement Learning for LLMs using SkyRL and Ray.\
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40 mins | Intermediate\
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Open

Built with Ray. Deployed on Anyscale.

See how leading organizations take AI to production

12x \
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faster iteration to deliver over 100+ production models
5x \
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faster iteration for AI workloads
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Wenyue Liu\
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Senior ML Platform Engineer\
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“Ray and Anyscale aligned with our vision: to iterate faster, scale smarter, and operate more efficiently.”
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Sarah Sachs\
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Engineering Leader, AI Modeling\
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"We chose Anyscale not just for what we needed today, but for where we know we’re heading. As our AI workloads grow more complex, Anyscale gives us the infrastructure to scale without limits."
99% \
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reduction in cost
13x \
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faster model loading

The Team Behind Ray – On Your Team

Built by the creators of Ray. Supported by the people who know it best.

With Anyscale, you don’t just get a platform — you get a partner. Our team works hands-on with yours to troubleshoot, tune, and scale every part Ray-based platform, whether you're launching your first cluster or operating a large-scale deployment.

See Support Plans

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Try Anyscale Today

Unlock your potential – run AI and other Python applications on your cloud or on our fully-managed compute platform.

Get Started with $100 Credit

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