Beyond 'Does it Fit?': Unlocking LLM GPU Inference Concurrency with Memory Management
Deploying large language models on GPUs often hits an unexpected bottleneck: KV cache memory, not the model weights. Strategic quantization can dramatically increase user concurrency on existing hardware.