vLLM was initially introduced in a paper titled "[Efficient Memory Management for Large Language Model Serving with PagedAttention](https://arxiv.org/abs/2309.06180)," authored by Kwon et al. vLLM, short for Virtual Large Language Model, is an active open-source library designed to efficiently support inference and model serving for large language models (LLMs).

Pricing

Documentation: https://docs.vllm.ai/en/stable/#documentation
GitHub: https://github.com/vllm-project/vllm
Community: https://docs.vllm.ai/en/latest/community/meetups.html

There is no estimate or indication of the pricing by vLLM that is publicly available. However, it states that it is a cheap LLM serving everyone.

Things To Consider

vLLM requires significant customization to fit specific needs
In certain scenarios, the overhead associated with managing memory can reduce the anticipated performance gains.