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When to Use Encode-Prefill-Decode Disaggregation to Accelerate Multimodal Model Serving

1 min read Source: NVIDIA Generative AI

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Encode-prefill-decode (EPD) disaggregation is an inference optimization technique for multimodal models that separates the vision encoder stage from the prefill...

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Encode-prefill-decode (EPD) disaggregation is an inference optimization technique for multimodal models that separates the vision encoder stage from the prefill and decode stages. It is most effective for image-heavy prompts, short-to-medium outputs, and quantized mixture-of-experts (MoE) models. This post shows when and how to use EPD disaggregation with NVIDIA Dynamo to achieve up to 5x…

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Source: NVIDIA Generative AI • TrueVitaHub summary and available news coverage