In AI infrastructure, costs are increasingly determined by storage rather than just GPUs. Prices for DRAM chips have risen significantly over the past year, making efficient storage management a decisive factor for performance and cost-effectiveness. Companies that orchestrate storage wisely can significantly reduce token consumption and thus inference costs.
At the same time, caching strategies are becoming more complex, for example with longer prompt caching windows ranging from minutes to hours. Those who make optimal use of memory and improve cache processes gain a clear competitive advantage and can operate AI applications economically that were previously considered too expensive.