vLLM hosting: GPU server comparison
Are you looking for vLLM hosting on a powerful GPU server? Here you will find GPU server offerings for scalable LLM serving, high-performance inference, OpenAI-compatible APIs and the production deployment of large language models.
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Start tendervLLM GPU server for production model serving
vLLM is designed for the efficient delivery of large language models. A GPU server provides the compute and graphics memory required for low latency, high throughput and multiple concurrent requests.
What matters for a vLLM server?
The right hardware depends on model size, quantisation, context length and parallelism. Especially important are sufficient VRAM, high memory bandwidth, fast NVMe storage and reliable network connectivity. For models that do not fit on a single GPU, multi-GPU systems and distributed serving may be required.
Typical use cases
- OpenAI-compatible inference APIs
- RAG applications and internal AI assistants
- scalable serving for multiple users
- batch inference and automated processing
- deployment of various open-source LLMs
Comparing vLLM with other serving frameworks
vLLM is particularly well suited for production inference and high utilisation. Alternatives include SGLang GPU server or a general LLM GPU server. Compare GPU, VRAM, billing, scaling and operating system support appropriate to your model.