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Co-Designing AI Model Attention for Fast, Interactive Long-Context Inference
TL

Tanya Lenz

· 1 min read

EngineeringNVIDIA Technical Blog

Co-Designing AI Model Attention for Fast, Interactive Long-Context Inference

As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1). Because...

As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1). Because attention now dominates that cost, how it is designed—not just how it is implemented—increasingly determines a model’s inference performance. Shaping model architecture around how GPUs execute it is the premise of AI model co-design.

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This story was published by NVIDIA Technical Blog and written by Tanya Lenz. SyncAI.news shows a preview; the complete article is on the publisher's site.

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