Baseten

Truss is Baseten's open-source Python-native SDK designed to package and deploy machine learning models seamlessly. It allows you to define your model's environment, dependencies, and pre/post-processing logic in a way that ensures consistency between your local development environment and Baseten's production infrastructure.

Yes, Baseten provides robust autoscaling capabilities that automatically adjust compute resources based on real-time demand. This ensures your model-backed applications remain responsive during traffic spikes while scaling down to zero or minimum levels during idle periods to optimize costs.

Baseten offers a variety of GPU instances to suit different model requirements, ranging from cost-effective options for smaller models to high-performance hardware for large-scale LLMs. Users can specify their hardware requirements within their model configuration to ensure optimal performance.

With the Truss SDK, the transition from local development to a production-ready API endpoint can often be completed in minutes. By running a few simple commands, Baseten handles the containerization, provisioning, and scaling logic automatically.

Yes, Baseten is designed to work seamlessly with Hugging Face. You can quickly pull popular open-source models, fine-tune them if necessary, and deploy them using Baseten's infrastructure to take advantage of optimized GPU serving and autoscaling.

Baseten is framework-agnostic and provides native support for popular libraries including PyTorch, TensorFlow, and Hugging Face. You can easily import models from these frameworks and use the Truss SDK to handle the containerization and deployment process.

Absolutely. Once a model is deployed on Baseten, it is exposed via a secure REST API endpoint. This allows you to integrate model inference into any application, regardless of the frontend or backend stack, by making standard HTTP requests.

On the Basic plan, you are billed based on the actual compute time your models consume during inference. This usage-based model is ideal for developers and startups who want to deploy custom or open-source models without the burden of high upfront monthly platform fees.

The Enterprise plan is designed for organizations requiring maximum control, offering self-hosted deployment options within your own VPC. It also includes custom Service Level Agreements (SLAs), dedicated support, and advanced security features tailored for large-scale corporate environments.

Baseten employs industry-standard security practices, including encryption at rest and in transit, to protect your intellectual property. For customers with strict data residency requirements, the Enterprise plan allows for deployments within your own cloud perimeter to maintain total data sovereignty.

Yes, through our Enterprise tier, we support self-hosted deployments and private clusters. This ensures that your inference workloads and sensitive data never leave your controlled environment, meeting the highest standards for corporate compliance and privacy.

All users have access to our comprehensive technical documentation and community resources. Pro and Enterprise customers receive priority support, with Enterprise clients benefiting from dedicated account management and custom support response times.