
From startups to enterprises, businesses of all sizes are quickly realizing that using custom, fine-
tuned, or open-source AI models has become essential for building competitive products.
At the same time, using these models in production presents challenges around reliability, security,
and performance. While AI providers like Anthropic and OpenAI can serve as a starting point, they
fall short for enterprise-grade solutions. Organizations need greater control over model behavior,
data privacy, and scalability—without sacrificing performance.
Choosing the right hosting solution is key to overcoming these challenges. Where you run your
inference workloads—on a cloud platform, your own virtual private cloud (VPC), or using a hybrid
approach—directly impacts the effectiveness of your AI systems. This choice is particularly
important when it comes to AI inference, the process of running models to generate responses or
predictions from new data.
Effective inference is vital for real-time services, seamless user experiences, and data-driven
decision-making. As businesses increasingly rely on AI to drive results, the need for efficient,
secure, and scalable hosting solutions has never been more urgent. Companies with superior
infrastructure will hold a competitive edge.
Baseten is laser-focused on providing the most performant and customizable deployment options
tailored to organizational needs. Unlike other infrastructure providers, with Baseten, you can run
your inference workloads in your cloud, our cloud, or both. As a result, our customers achieve lower
costs, industry-leading latencies, and 100% uptime—delivering powerful user experiences.
For CIOs, CTOs, VPs of AI, and IT leaders, understanding the benefits of different hosting solutions
is critical to ensuring performance, compliance, and cost-efficiency for AI-powered products. In
this guide, we’ll explore the differences between cloud, self-hosted, and hybrid hosting solutions,
and how they can play a key role in successful AI initiatives.
Introduction
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