Run vLLM on Runpod Serverless: Deploy Open Source LLMs in Minutes

The blog discusses choosing between closed source and open source large language models (LLMs), focusing on factors such as cost efficiency, performance, and data security. It highlights that while closed source models like OpenAI's ChatGPT are convenient and powerful, open source models like Meta's Llama-7b offer tailored performance, cost savings, and enhanced data privacy, making them suitable for specific applications and scalable needs. The blog introduces vLLM, a high-performance inference engine that significantly boosts throughput for open source models using a memory allocation algorithm called PagedAttention. It supports numerous LLMs and is compatible with various GPU architectures, making it a versatile choice for deploying models efficiently. The blog provides a step-by-step guide for deploying an open source LLM using vLLM on the Runpod Serverless platform, emphasizing ease of use and offering troubleshooting tips for common deployment issues.

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