https://www.elastix.ai/blog daily 0.75 2026-02-25 https://www.elastix.ai/blog/five-reasons-why-fpgas-hit-the-sweet-spot-for-llm-inference-jk2ds monthly 0.5 2026-02-25 https://images.squarespace-cdn.com/content/v1/697bc10e1897a6304e62d6e3/b985407c-2f82-4522-9569-31ca2b367e00/Arithmetic+Intensity_pages-to-jpg-0001.jpg Blog - How ElastixAI Delivers the Lowest Cost per Token in LLM Inference - Make it stand out Typical batch sizes for MoE models inference require arithmetic intensities of <100, causing extremely low compute utilization on B200. https://images.squarespace-cdn.com/content/v1/697bc10e1897a6304e62d6e3/acbe35ad-5dc9-4425-a1af-3c9f1ed36716/Frictionless+Drop-In_pages-to-jpg-0001.jpg Blog - How ElastixAI Delivers the Lowest Cost per Token in LLM Inference - Make it stand out ElastixAI’s co-design workflow. https://www.elastix.ai/blog/five-reasons-why-fpgas-hit-the-sweet-spot-for-llm-inference monthly 0.5 2026-02-25 https://images.squarespace-cdn.com/content/v1/697bc10e1897a6304e62d6e3/b985407c-2f82-4522-9569-31ca2b367e00/Arithmetic+Intensity_pages-to-jpg-0001.jpg Blog - Five Reasons Why FPGAs Hit the Sweet Spot for LLM Inference - Make it stand out Typical batch sizes for MoE models inference during the decode phase require arithmetic intensities of <100, causing extremely low compute utilization on B200 for LLM inference. https://images.squarespace-cdn.com/content/v1/697bc10e1897a6304e62d6e3/ad462bd6-ba6b-4553-bace-d7041e97979e/Chart.png Blog - Five Reasons Why FPGAs Hit the Sweet Spot for LLM Inference - Make it stand out Cost per million output tokens vs. interactivity. 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