# Neuralwatt says cache misses can use up to 140% more inference energy

> Source: <https://runtimewire.com/article/neuralwatt-harness-cache-energy-chad-gibson>
> Published: 2026-10-17 01:30:14+00:00

# Neuralwatt says cache misses can use up to 140% more inference energy

**CEO Chad Gibson's analysis of Neuralwatt Cloud traffic links prompt edits to wasted GPU work, with the biggest costs in long agent sessions.**

        By [Ryan Merket](https://runtimewire.com/author/ryan-merket)
        · Published 

Primary source: [Neuralwatt](https://neuralwatt.com/news/why-harnesses-matter-for-energy-efficiency)

## Why it matters

Neuralwatt's traffic analysis makes the agent harness an efficiency variable alongside models and GPUs. If the findings hold across other deployments, prompt construction gives teams a software-level way to cut repeated inference work, especially in long-running agents.

[Neuralwatt](https://neuralwatt.com/?ref=runtimewire) CEO [Chad Gibson](https://www.linkedin.com/in/chad-c-gibson?ref=runtimewire) says the software that sends prompts to an AI model can nearly double the energy required to serve a request. In an [analysis published October 16th](https://neuralwatt.com/news/why-harnesses-matter-for-energy-efficiency?ref=runtimewire), Neuralwatt compared prompt-cache reuse across agent clients and found that small differences in how they assemble prompts can translate into substantial extra prefill work.…