# Welcome to Q Blocks

[**Q Blocks**](https://www.qblocks.cloud/) is a new kind of GPU cloud solution designed for AI model training, tuning, and deployment workloads. Our platform is built using a distributed computing approach, allowing us to offer upto 80% more affordable and scalable GPU cloud services compared to other cloud providers.

With Q Blocks, you can easily port your existing workloads to our platform without any code changes. All GPU instances are containerised, ensuring seamless integration with your current workflows.

We have state of the art Nvidia GPU instances to offer in single and multi-GPU configurations to help you train and deploy small as well as large ML models.

Our platform is also highly decentralised, which means we can orchestrate container-native workloads at scale across a grid of heterogeneous machines, including consumer and data center nodes.

![](https://2367841498-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-M9O-9uez85Lp9ysQP3O%2Fuploads%2FXjJMqADPQQxowf53aqDw%2Fhow%20qb%20works.001.jpeg?alt=media\&token=6817d9c0-11a7-4c86-962a-36e99f7f119f)

At Q Blocks, we are committed to providing application-specific pipelines that enable the execution of the entire value chain for developers. Today, we offer a pipeline specifically designed for training and fine-tuning machine learning models.

We understand the importance of deploying and managing GPU instances at scale, and that's why we also offer Rest APIs to streamline the process of deploying and managing GPU instances for workloads like AI model inference.

Overall, Q Blocks is a powerful, affordable, and scalable solution for companies looking to streamline their AI model training, tuning, and deployment workflows.


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