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TurboML provides flexible pricing options tailored to your needs, whether you are just getting started or running advanced machine learning workloads at scale. Choose the plan that suits you best:

Pro

For growing businesses

Popular
$0.01/TBU

Billed on the basis of usage

Access to CPU & GPU Instances

Triggers & Automations

Experiment Tracking

Cost & Usage Tracking

Priority Technical Support

SLA for Critical Cases

Ideal for: Small to medium-sized businesses scaling machine learning operations.

Enterprise

For large enterprises

Premium
Custom Pricing

Contact sales for more info

Custom SLA

Audit Trails

SSO & Role-Based Access

99.9% Uptime Guarantee

Advanced Security & Compliance

Dedicated Account Manager

Ideal for: Large enterprises with complex ML workloads and hybrid infrastructure requirements.

FeaturesProEnterprise
Access to CPU & GPU InstancesSupportedSupported
Triggers & AutomationsSupportedSupported
Experiment TrackingSupportedSupported
Cost & Usage TrackingSupportedSupported
Operational & Model Deployment FeaturesSupportedSupported
Host, Serve & Monitor Custom ModelsSupportedSupported
Custom MetricsSupportedSupported
SLA for Critical Cases (<3 hrs)SupportedSupported
Priority Technical SupportSupportedSupported
Audit TrailsNot supportedSupported
Custom SLANot supportedSupported
RBAC & SSO SupportNot supportedSupported
Advanced Security & ComplianceNot supportedSupported
Self-Hosted Hybrid DeploymentsNot supportedSupported
Customizable TBU PackagesNot supportedSupported
200+ Data Sources & Custom ConnectorsNot supportedSupported
Dedicated Account ManagerNot supportedSupported
Advanced Security & Compliance (SOC 2, GDPR, HIPAA)SupportedSupported

TurboML Instance Types

TurboML provides a versatile selection of instance types designed to meet a variety of deployment needs. With flexible CPU and memory configurations, our general-purpose instances allow you to optimize for both performance and efficiency. Explore the instance sizes to find the perfect match for your requirements.

InstanceCPUMemoryTBU
tiny12 GB25
small28 GB50
medium416 GB100
large832 GB200
xlarge1664 GB400
2xlarge32128 GB800
4xlarge64256 GB1600
8xlarge128512 GB3200
12xlarge192768 GB4800

TurboML offers a diverse range of GPU-powered instances tailored for efficient training and deployment of machine learning models. Powered by NVIDIA GPUs like A10G, T4, and A100, these instances deliver exceptional performance to meet the demands of your workloads.

InstanceGPU TypeGPUsCPUMemoryTBU
gpu1.smallNVIDIA A10G1416 GB150
gpu1.mediumNVIDIA A10G1832 GB180
gpu1.largeNVIDIA A10G11664 GB240
gpu1.xlargeNVIDIA A10G132128 GB375
gpu1.2xlargeNVIDIA A10G448192 GB700
gpu2.smallNVIDIA T41416 GB75
gpu2.mediumNVIDIA T41832 GB100
gpu2.largeNVIDIA T411664 GB180
gpu3.smallNVIDIA L41416 GB120
gpu3.mediumNVIDIA L41832 GB150
gpu3.largeNVIDIA L411664 GB190
gpu3.xlargeNVIDIA L4132128 GB300
gpu4.largeNVIDIA A1001461 GB150
gpu4.8xlargeNVIDIA A100832488 GB1000
gpu5.48xlargeNVIDIA H10081922048 GB15000

TurboML Billing Units (TBU) Pricing Model

TurboML provides a straightforward and flexible billing system based on TurboML Billing Units (TBU), allowing you to pay only for what you use. This predictable pricing model adapts to the needs of organizations of all sizes, ensuring cost efficiency.

What is a TurboML Billing Unit (TBU)?

A TurboML Billing Unit (TBU) is the core metric for usage-based billing on the TurboML platform. It represents the normalized cost of operations such as data processing, storage, and retrieval. Your monthly costs are calculated based on the number of TBUs consumed across various activities like retrieval, and storage.

1 TBU = $0.01

Your monthly charges will depend on the number of TBUs consumed across various operations such as data ingestion, data retrieval, and data storage.

How TBUs are Consumed

1. Data Retrieval (Reads):
Accessing or querying data from TurboML incurs TBUs based on the size of the data retrieved.
Example: Retrieving 1 GB of data may cost 500 TBUs.

2. Data Storage:
Storing data on the TurboML platform is charged based on the volume stored and the storage duration.
Example: Storing 1 GB of data per hour may cost 0.05 TBUs.

3. Instance Types:
Running workloads on TurboML involves charges for compute resources based on instance types. Larger instances consume more TBUs per hour.

Billing Examples with Instance Types

Scenario 1: Small-Scale Use Case (General-Purpose Instances)
A small organization deploys eight "Large" instance types at a rate of 200 TBUs/hour.
• Instance Usage: 8 instances x 200 TBUs/hour x 24 hours x 30 days
• Estimated TBUs Used: 1,152,000 TBUs

Scenario 2: Enterprise Use Case (General-Purpose Instances)
An enterprise deploys sixteen "2xLarge" instance types at a rate of 800 TBUs/hour.
• Instance Usage: 16 instances x 800 TBUs/hour x 24 hours x 30 days
• Estimated TBUs Used: 9,216,000 TBUs

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Why TurboML?

Flexible Deployment: Choose from major clouds or hybrid on-prem for Enterprise plans.
Scalable: Pay only for the resources you use with our TBU-based pricing model.
Reliable: Enterprise-grade security and support for mission-critical workloads.

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