Mystic

Mystic provides a fully managed platform to deploy models directly in your own cloud account, optimizing costs and performance.

Mystic's shared cluster allows low-cost pay-as-you-go access to GPUs, though performance depends on real-time availability.

Mystic optimizes costs by running on spot instances, parallelizing models on the same GPU, and automatically scaling down to 0 GPUs when not in use.

Mystic supports various inference engines like vLLM, TensorRT, Deepspeed, and Exllama, allowing you to bring your own.

Mystic provides APIs, CLI, and Python SDK to deploy models without Kubernetes or DevOps expertise, along with a dashboard to manage deployments.

Mystic offers two options: deploying models directly in your own AWS, Azure or GCP cloud account, or using Mystic's shared GPU cluster on a pay-as-you-go basis.

Mystic optimizes costs by running on spot instances, parallelizing models on the same GPU, and automatically scaling down to 0 GPUs when not in use.

Mystic supports various inference engines like vLLM, TensorRT, Deepspeed, and Exllama, allowing you to bring your own.

No, Mystic provides APIs, CLI, and Python SDK to deploy models without Kubernetes or DevOps expertise.

You can get started by visiting the Mystic website at https://www.mystic.ai and exploring their deployment options and pricing.