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.
Llama 3.3 Swallow: A superior 70B parameter Japanese LLM trained on AWS, outperforming GPT-4o-mini. Open-source, with instruction-tuned & base model variants.
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