Baseten
AI inference infrastructure for deploying and scaling production models.
What is Baseten?
Baseten is an AI inference platform for teams that need to deploy, operate, and scale models in production. It supports open-source, custom, and fine-tuned models on infrastructure designed for high-performance inference.
The platform combines dedicated deployments with model APIs for testing and serving supported models. Teams can also run training workloads and then move models onto the same stack for production inference.
Baseten offers managed cloud deployments as well as self-hosted options for organizations that need to run inside their own VPCs. Its multi-cloud positioning makes it a fit for engineering teams balancing latency, capacity, and isolation requirements.
The product covers several generative-AI modalities, including image generation, transcription, text-to-speech, large language models, embeddings, and compound AI systems. It is aimed at developers and product teams building AI features that require production-grade model serving.
Pricing is usage-based for compute, with published per-minute rates for dedicated deployments and model APIs. Larger Pro and Enterprise arrangements may include negotiated compute discounts.
Baseten Features
Dedicated model inference
Baseten supports dedicated inference for open-source, custom, and fine-tuned models. That makes it suitable for teams that need to serve specialized models rather than only consume a fixed catalog of APIs.
Model APIs and training workflows
The platform provides pre-optimized model APIs for evaluating and prototyping workloads. It also supports training through the Loops SDK and deployment to production inference on the same stack.
Cloud, self-hosted, and hybrid deployment
Baseten can run as a managed cloud offering or inside an organization’s own VPCs. These deployment options give teams a choice between managed operations, dedicated isolation, and hybrid capacity.
Generative AI modality support
The inference stack is positioned for image generation, speech workloads, language models, embeddings, and compound AI applications. This lets one deployment platform address multiple model modalities as products expand.
Pricing
Paid
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