Alternatives to Vllm
6 alternatives found
vLLM is an open-source high-throughput and memory-efficient LLM inference and serving engine, created by Woosuk Kwon, Zhuohan Li, and colleagues at UC Berkeley in 2023. vLLM's breakthrough innovation is PagedAttention — a memory management technique inspired by virtual memory paging in OS kernels that eliminates memory fragmentation in the KV cache, increasing GPU memory utilization from ~60% (with naive continuous batching) to 96%+.
Ollama
Local single-user inference — Ollama for developer laptops, vLLM for GPU cluster production serving
TGI
Hugging Face Text Generation Inference — comparable production server, different optimization stack
TensorRT-LLM
NVIDIA's LLM inference optimizer — maximum NVIDIA GPU throughput with more complex setup than vLLM
Ray Serve
Scalable model serving framework — vLLM often runs inside Ray Serve for distributed GPU fleets
SageMaker
AWS managed ML serving — SageMaker can serve vLLM containers for managed inference endpoints
Triton
NVIDIA Triton Inference Server — enterprise model serving supporting TensorRT-LLM and vLLM backends
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