Q.How is my bill calculated?
A.Contact Anyscale's sales team for a custom quote.
A
Anyscale | Scalable Compute for AI and Python
★4.5
💬13051
💲Paid
Anyscale is an AI application platform that enables developers to build, run, and scale AI applications efficiently. It leverages Ray's distributed computing framework to optimize performance and reduce costs, offering tools for compute governance, developer tooling, and flexible deployment options.
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Platform
web
AI InfrastructureAI PlatformCloud ComputingCompute GovernanceDeep LearningDistributed ComputingGPU Acceleration
What is Anyscale | Scalable Compute for AI and Python?
Anyscale is an AI application platform designed for developers to build, run, and scale AI applications instantly. It uses the Ray distributed computing framework to optimize performance and reduce costs for AI workloads, offering tools for compute governance, developer tooling, and flexible deployment across any cloud, accelerator, and stack.
Core Technologies
- Ray Distributed Computing Framework
- RayTurbo
- GPU Acceleration
- Cloud Computing
Key Capabilities
- Build and scale AI applications
- Optimize AI compute performance
- Manage AI usage with compute governance
- Support for any cloud, accelerator, and stack
Use Cases
- Scaling distributed ML workloads across GPUs and CPUs
- Building AI applications with lasting impact
- Maximizing throughput for optimized cost
- Parallelizing thousands of small- and mid-sized models
Core Benefits
- Accelerates model training and deployment
- Reduces latency and improves cost efficiency
- Offers flexible deployment options (cloud, on-premise, hybrid)
- Enables scalable distributed programs for LLM pipelines
Key Features
- RayTurbo for optimized AI compute
- Compute governance tools
- World-class developer tooling
- Support for any cloud, accelerator, and stack
How to Use
- 1Leverage Ray's Pythonic APIs to run workloads
- 2Optimize performance and manage resources
- 3Deploy AI applications in cloud, on-premise, or hybrid setups
- 4Get started with a $100 credit
- 5Explore features through demos and expert consultations
Pricing Plans
CPU Only
from $0.00006 /min
Deploy in Your Cloud
NVIDIA T4
from $0.00246 /min
Deploy in Your Cloud
NVIDIA L4
from $0.00414 /min
Deploy in Your Cloud
NVIDIA A10G
from $0.00591 /min
Deploy in Your Cloud
NVIDIA L40S
from $0.01089 /min
Deploy in Your Cloud
NVIDIA Tesla V100
from $0.01492 /min
Deploy in Your Cloud
NVIDIA A100 40GB
from $0.02149 /min
Deploy in Your Cloud
NVIDIA A100 80GB
from $0.02941 /min
Deploy in Your Cloud
AWS Trainium1
from $0.00784 /min
Deploy in Your Cloud
AWS Inferentia2
from $0.00445 /min
Deploy in Your Cloud
CPU Only
from $0.00855 /min
Deploy in Anyscale’s Cloud
NVIDIA T4
from $0.01643 /min
Deploy in Anyscale’s Cloud
NVIDIA L4
from $0.01811 /min
Deploy in Anyscale’s Cloud
NVIDIA A10G
from $0.02723 /min
Deploy in Anyscale’s Cloud
NVIDIA Tesla V100
from $0.06646 /min
Deploy in Anyscale’s Cloud
NVIDIA A100 80GB
from $0.11312 /min
Deploy in Anyscale’s Cloud
Frequently Asked Questions
Q.Does Anyscale provide training for Ray and Anyscale?
A.Yes, you can work with the Ray creators to deliver and optimize your AI workloads.
Q.Do you provide support options?
A.Yes, you can get Ray support from Anyscale.
Q.Are there bulk discounts available?
A.Yes, volume discounts on compute are available. Contact the sales team for a custom quote.
Pros & Cons (Reserved)
✓ Pros
- Enables scalable distributed programs for LLM pipelines
- Accelerates model training and deployment
- Reduces latency and improves cost efficiency
- Offers flexible deployment options (cloud, on-premise, hybrid)
✗ Cons
- May require familiarity with Ray and distributed computing concepts
- Pricing can be complex depending on usage and deployment environment
Alternatives
No alternatives found.