vLLM vs TensorRT-LLM vs TGI vs SGLang — how do you pick?
mediumAnswer
- vLLM: open-source, easy to install, wide model support, strong throughput.
- TensorRT-LLM: NVIDIA's optimized engine (compiled kernels), best raw performance on H100 but complex to build.
- TGI (HuggingFace): production-friendly, good streaming, decent perf.
- SGLang: high-perf, native support for structured / constrained decoding, growing ecosystem.
- For most teams: vLLM by default.
- Move to TensorRT-LLM if squeezing every % matters at scale.
- TGI for HF ecosystem integration.
- SGLang for heavy structured output workloads.
Check yourself — multiple choice
- All identical
- vLLM: default OSS; TensorRT-LLM: peak perf on NVIDIA; TGI: HF ecosystem; SGLang: structured output — pick per workload / stack
- Only TGI
- Same performance
Serving engines: vLLM default; TRT-LLM peak; TGI HF-friendly; SGLang structured-output focus.
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