vllm and ZhiLight
vLLM is a general-purpose inference engine supporting diverse model architectures, while ZhiLight is a specialized acceleration layer optimized specifically for Llama variants, making them complements that can work together where ZhiLight provides Llama-specific optimizations on top of or alongside vLLM's broader serving infrastructure.
About vllm
vllm-project/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs
Implements PagedAttention for efficient KV cache management and continuous request batching to maximize GPU utilization. Supports multiple quantization schemes (GPTQ, AWQ, INT4/8, FP8), speculative decoding, and tensor/pipeline parallelism across NVIDIA, AMD, Intel, and TPU hardware. Provides OpenAI-compatible API endpoints and integrates directly with Hugging Face models, including multi-modal and mixture-of-expert architectures.
About ZhiLight
zhihu/ZhiLight
A highly optimized LLM inference acceleration engine for Llama and its variants.
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