SGLang uses less GPU memory and delivers better performance due to its efficient memory management and batch scheduling. It only imports some fused kernels and layers from vLLM, using vLLM as a kernel library, which allows it to optimize memory usage and throughput effectively. This results in SGLang using significantly less memory for the same tasks compared to vLLM, which pre-allocates a large portion of GPU memory for its operations, including KV caching (source, source).
Would you like more detail on how SGLang achieves these optimizations?
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