vLLM
Definition
vLLM is a runtime environment for efficient deployment of large language models.
It organizes model inference and incoming requests, including efficient memory management and shared processing. Available features depend on model, hardware, and version.
Simply explained
Like a job scheduler that processes multiple model requests as efficiently as possible on the same machine.
Why it matters in practice
Language models can be operated at higher utilization than individually started model calls.
Example from business
Hypothetical example: A company provides an open language model for multiple internal applications.
Limits and pitfalls
- High throughput does not equal low response time; memory requirements and concurrency must be tested together.
Origin & history
vLLM was developed as a specialized system for serving large language models.
Use in mid-sized companies
- Operate internal model endpoints and measure under real load.
Frequently asked questions
Is vLLM itself a trained language model?
No, it runs suitable models.
Sources
- Documentation · vLLM: Documentation –
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