Pricing

Start free, scale seamlessly.

Choose your preferred storage, inference, and number of instances, and we’ll provide you with an estimated cost.
Easy – just like the rest of Marqo.

Cloud

From $499 per month

Features

Fully managed

End-to-end vector creation and storage

Horizontally scalable

Model Customization

CPU instances and GPU instances

Scale at the click of a button

Access control

High availability

Low latency

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Enterprise

Custom Quotes

Tailored to your needs

Features

All the functionality of Marqo Cloud

SSO

Single tenant deployment

Observability Integrations

24/7/365 dedicated support

Migration assistance

Access to ML scientists

VPC deployment (+add on)

Enhanced Enterprise SLA

Sizing assistance

Dedicated slack channel

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Marqtune

Custom Quotes

Customized for you

Features

Fine-tune embedding models

Generalized Contrastive Learning

Flexible training datasets

Wide range of base models

Train with historical sales data

Model evaluation

Access to ML scientists

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Frequently Asked Questions

What is vector search?

Vector search allows you to search documents, images and other data by converting items into a collection of vectors. This collection of vectors summarises the data in semantic form and allows us not only to match documents against queries through analysis of the semantic content, but also to understand where and how the document matched the query. With Marqo, inference to create the vectors is included.

What is the best setup for my application?

The number of instances you will need depends on a number of factors. The number of documents, the size of the documents and the type of data (image vs text). When dealing with low search volumes that primarily involve text or when low latency is not crucial, using CPU inference nodes can be a cost-effective solution. On the other hand, GPU inference nodes provide a significant performance boost when indexing and searching with images and are recommended for indexing large datasets and processing high volume, low latency searches. For multimodal models marqo.CPU.large is recommended as a minimum.

The estimates for storage capacity provided in our calculator assume your are using a model that produces 768 dim. vectors.

Do I have to change my code to move from open-source to cloud?

The only changes you need to make are to update your URL and API key when accessing Marqo.

How does billing work?

You will be billed at the end of the month for total inference and shard hours used. Usage is rounded up to 15-minute increments.

Request a demo

We’d love to speak with you. Send us your questions about Marqo and we’ll set up a time to meet with you.

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