# HPE storage reuses AI inference cache to speed multi-agent workloads

- URL: https://talkfuse.com/story/hpe-puts-storage-to-work-on-ais-expensive-memory-problem/
- Published: 2026-10-29T09:00:00+00:00
- Updated: 2026-10-29T09:08:08+00:00
- Original publisher: The Register
- Original article: https://www.theregister.com/storage/2026/10/29/partner-content-hpe-puts-storage-to-work-on-ais-expensive-memory-problem/5305793
- Topics: Art, Culture

## Key points

- HPE storage can retain AI inference cache outside GPU memory.
- A Kamiwaza-validated test reported up to 20 times faster first tokens.
- Results depend on workload and cache reuse.

## Summary

HPE is positioning its Alletra MP X10000 storage system as a way to retain AI inference cache that would otherwise be removed from scarce GPU memory. Reusing this stored state can reduce repeated calculations, potentially cutting response times and improving accelerator use in multi-agent workloads.

In testing validated by Kamiwaza, using NVIDIA H200 GPUs and the Nemotron 70B model with more than 30 concurrent agents, cache offload delivered up to 20 times faster time to first token and 17 times higher effective inference throughput than running without it. The gains depend on factors such as context length, concurrency, cache hit rates and data transfer overhead, so they are not guaranteed for every workload.

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Summarised by TalkFuse (https://talkfuse.com/). Quote the original publisher for the reporting and link this page for the summary and discussion.