II.
Tool overview
Reference · livetool:vllm
vLLM overview
High-throughput and memory-efficient LLM inference engine implementing the PagedAttention algorithm to maximise GPU KV-cache utilisation. Exposes an OpenAI-compatible REST API and supports continuous batching, streaming, and tensor parallelism across multiple GPUs. A common production serving backend for self-hosted open-source language models.
Attributes
displayName
vLLM
homepageUrl
kind
other
description
High-throughput and memory-efficient LLM inference engine implementing the
PagedAttention algorithm to maximise GPU KV-cache utilisation. Exposes an
OpenAI-compatible REST API and supports continuous batching, streaming, and
tensor parallelism across multiple GPUs. A common production serving
backend for self-hosted open-source language models.
Outgoing edges
alternative_to3
- tool:tensorrt·ToolTensorRT
- tool:triton-inference·ToolTriton Inference Server
- tool:onnx-runtime·ToolONNX Runtime
belongs_to_language1
- language:python·LanguagePython
tool_used_by2
- skill-area:model-serving·SkillAreaModel Serving
- skill-area:llm-infrastructure·SkillAreaLLM Infrastructure
used_for2
- skill-area:model-serving·SkillAreaModel Serving
- skill-area:ai-evaluation·SkillAreaAI Evaluation
Incoming edges
alternative_to3
- tool:tensorrt·ToolTensorRT
- tool:triton-inference·ToolTriton Inference Server
- tool:onnx-runtime·ToolONNX Runtime
composed_of1
- stack-profile:llm-fine-tuning·StackProfileLLM Fine-Tuning Stack (PyTorch, HuggingFace, PEFT/LoRA, W&B, vLLM)
uses_tool2
- specialization:ml-inference-serving·SpecializationML Inference Serving
- specialization:gpu-programming·Specialization