DeepSeek vs Qwen: local model showdown featuring LaunchDarkly AI Configs

This tutorial demonstrates how to run large language models locally using Ollama and query the results from a Node.js application. It also shows how to create a custom model AI config with LaunchDarkly that tracks metrics such as latency, token usage, and generation count. The tutorial covers the benefits of running LLMs on local hardware, including enhanced data privacy, accessibility, and sustainability. It provides instructions on how to install Ollama, connect it to Node.js, and create a custom model AI config using LaunchDarkly. The tutorial also includes examples of how to use the custom model AI config to generate responses from different models and track metrics such as latency, token usage, and generation count.

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