[Blog]: multimodal blog - #470
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Signed-off-by: Xiyue Yu <xiyue@google.com>
capri-xiyue
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August 11, 2026 20:14
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Signed-off-by: Xiyue Yu <xiyue@google.com>
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assign @ahg-g |
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assign @roytman |
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| Reach for disaggregation when the encoder is genuinely the bottleneck: a high multimodal-to-text ratio, several large assets per request, or a ViT heavy enough that running it inline visibly stalls decode. | ||
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| And be honest about the crossover. SGLang's report is blunt on this, and it applies equally here: for image-light workloads the network latency of shipping embeddings can outweigh the time saved by offloading, **raising** TTFT relative to collocation while dedicated encoder GPUs sit idle. Disaggregation is most efficient exactly when visual processing is the primary bottleneck. If it is not, you are paying for a tier and a network hop to solve a problem you do not have. |
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which SGLang report are you referring here? Maybe add a link to it for clarity.
Signed-off-by: Xiyue Yu <xiyue@google.com>
Signed-off-by: Xiyue Yu <xiyue@google.com>
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