Models

Foundation models and LLMs power modern AI applications, from content generation to semantic search and code completion. Whether you're building a chatbot, search engine, or generative feature, you need access to pre-trained models via API or self-hosted deployment. Model providers offer varying levels of customization, performance, and cost—choosing the right one depends on your use case, latency requirements, and data sensitivity.

When evaluating model providers, consider API pricing and token costs, inference speed and availability, model capabilities (language, vision, or multimodal), fine-tuning options, and compliance certifications for regulated industries. Integration with your existing stack—vector databases, orchestration frameworks, and monitoring tools—also matters. Some builders prioritize open-weight models for privacy and control; others rely on closed APIs for cutting-edge performance.

Shyft's Models directory helps you compare 28+ providers side-by-side. Use filters to narrow by model type, deployment method (API vs. self-hosted), pricing model, and supported features. Each listing includes pricing transparency, integration options, and real-world use cases so you can match your requirements to the right provider without vendor lock-in assumptions.