The article argues that enterprises should measure AI infrastructure economics by cost per token rather than raw compute metrics like FLOPS per dollar. It shows how maximizing delivered tokens—through hardware, software and system optimizations—drives down real-world cost and boosts revenue, citing NVIDIA Blackwell’s 35× lower token cost versus Hopper.

Liquid AI has launched the LFM2.5-350M, an enhanced version of its 350M model, featuring 28 trillion tokens of pre-training and improved performance in data extraction and tool use. The model runs efficiently on various hardware, making it suitable for large-scale data pipelines and edge deployments.