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pulse NVIDIA Technical Blog September 09, 2026

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

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

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

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