Discover llm-d on AWS for efficient LLM inference. Boost performance, maximize GPU utilization, and cut costs with disaggregated serving, intelligent scheduling, and EFA-powered communication.
P-EAGLE in vLLM boosts LLM inference by up to 1.69x. Parallel speculative decoding drafts tokens in one pass for higher throughput and acceptance rates. Simple to integrate.
Discover how AWS’s updated Large Model Inference (LMI) container enhances LLM performance and reduces costs with LMCache, EAGLE decoding, and improved LoRA support.
The information provided on this website is provided for entertainment purposes only. We make no representations or warranties, expressed or implied, about the information. This includes its completeness, accuracy, adequacy, legality, usefulness, reliability, suitability, and availability. We also make no claims about anything else. Any reliance you place on the information is strictly your own responsibility. We accept payment from advertisers and sponsors with relevant ads. We may recommend products on our website and get paid to advertise them. You can find additional terms in the terms of use.
