Stop Wasting Your Multi-GPU Setup With llama.cpp : Use vLLM or ExLlamaV2 for Tensor Parallelism · Osman's Odyssey: Byte & Build

Multi-GPU setups are being underutilized when using llama.cpp for LLM inference. For optimal performance with multiple GPUs, vLLM and ExLlamaV2 provide tensor parallelism and batch inference capabilities that can achieve 800 tokens per second with 50 concurrent requests, compared to llama.cpp's sequential processing. The article explains when to use each inference engine: llama.cpp only for CPU offloading scenarios, vLLM for high-performance multi-GPU batch inference, and ExLlamaV2 for memory-efficient quantized models with tensor parallelism support.