A checklist for switching to open source ML models

Switching from a closed source ecosystem where you consume ML models from API endpoints to the world of open source ML models can seem intimidating, but it offers a vast number of models and flexibility in customization options. Choosing an appropriate GPU for model inference is crucial as some models require powerful GPUs while others can run on less expensive ones. Optimizing latency, throughput, quality, and cost is also possible with open source models, allowing users to align their use case requirements. Deploying and integrating the new model endpoint is a necessary step after selecting the right hardware configuration and optimizing the model for the desired outcome.

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