Atlas · GenAI 2026
LLM Inference Serving
High-throughput inference engines (vLLM, TGI, TensorRT-LLM, SGLang, Triton)
conceptPeak: 2024Serving RuntimesAI consensus: 3/3
Prerequisites
vLLM implements PagedAttention and KV cache management for Transformers — understanding what KV cache is requires Transformer knowledge
- mediumDocker
Production vLLM deployment typically runs in containers
Recommended reference
docs.vllm.ai — vLLM docs; plus Kwon et al. (2023) 'Efficient Memory Management for LLM Serving with PagedAttention' paper
Notes from AI deep research
Anthropic Opus
vLLM (TW Radar: Adopt!), TGI, TRT-LLM, SGLang, Triton. PagedAttention = standard
OpenAI Deep Research
vLLM [OA#56], TGI [OA#57], TensorRT-LLM [OA#59], Triton [OA#54]
Google Deep Think
Serwowanie dla setek użytkowników [G#71]
Related skills
- ← is part of: Inference Optimization(3/3)
- ← is part of: LLM Decoding Strategies(3/3)
- → is subcategory of: MLOps(3/3)
- ← is part of: Model Quantization(3/3)
- ← is an instance of: Ollama(3/3)
- ← is an instance of: Ray Serve(3/3)
- ← is subcategory of: Serverless AI(3/3)
- ← is an instance of: vLLM(3/3)
- ← is an instance of: BentoML(2/3)
- ← is an instance of: KServe(2/3)
- ← is part of: LLM API Gateway(2/3)
- ← is part of: LLM Observability(2/3)
- ← is part of: AI FinOps(1/3)
- ← is part of: LLM Testing(1/3)
- ← is an instance of: ONNX Runtime(0/3)
- ← is an instance of: NVIDIA Triton Inference Server(0/3)
- ← is an instance of: TorchServe(0/3)
- ← is an instance of: TensorRT-LLM(0/3)