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

<img width="768" height="432" src="https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-768x432.png" class="webfeedsFeaturedVisual wp-post-image" alt="" style="display: block; margin-bottom: 5px; clear:both;max-width: 100%;" link_thumbnail="" decoding="async" srcset="https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-768x432.png 768w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-179x101.png 179w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-300x169.png 300w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-625x352.png 625w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-1536x864.png 1536w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-645x363.png 645w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-660x370.png 660w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-500x281.png 500w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-160x90.png 160w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-362x204.png 362w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-196x110.png 196w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-1024x576.png 1024w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-960x540.png 960w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy.webp 1877w" sizes="(max-width: 768px) 100vw, 768px" title="llm-optimize-deploy" />As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1). Because...<img width="768" height="432" src="https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-768x432.png" class="webfeedsFeaturedVisual wp-post-image" alt="" style="display: block; margin-bottom: 5px; clear:both;max-width: 100%;" link_thumbnail="" decoding="async" loading="lazy" srcset="https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-768x432.png 768w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-179x101.png 179w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-300x169.png 300w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-625x352.png 625w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-1536x864.png 1536w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-645x363.png 645w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-660x370.png 660w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-500x281.png 500w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-160x90.png 160w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-362x204.png 362w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-196x110.png 196w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-1024x576.png 1024w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy-960x540.png 960w, https://developer-blogs.nvidia.com/wp-content/uploads/2026/07/llm-optimize-deploy.webp 1877w" sizes="auto, (max-width: 768px) 100vw, 768px" title="llm-optimize-deploy" /><p>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.</p> <p><a href="https://developer.nvidia.com/blog/co-designing-ai-model-attention-for-fast-interactive-long-context-inference/" rel="nofollow" data-wpel-link="internal" target="_self">Source</a></p>