Four Reasons Why FPGAs Hit the Sweet Spot for LLM Inference

For years, the industry has been taking a brute force approach to AI hardware. As AI models have changed in nature and complexity, most have responded by simply scaling the same rigid architectures to larger footprints. We’ve thrown High-Bandwidth Memory (HBM) and larger silicon dies at the challenge, yet the cost per token remains a barrier to truly ubiquitous AI. The fundamental mismatch is systemic. Large Language Models (LLMs) are advancing at a weekly cadence of algorithmic breakthroughs.