Alibaba Cloud optimizes GPU usage for LLM inferencing, cuts needs by 82%

Published 20/10/2025, 11:14
© Reuters

Investing.com -- Alibaba Cloud has published a paper detailing its Aegaeon GPU resource optimization solution for large language model (LLM) concurrent inferencing, the company announced Monday.

The cloud computing arm of Alibaba Group also revealed it successfully reduced the number of GPUs required by 82% in deployment through this new approach.

LLM inferencing typically involves numerous burst requests, which creates challenges for efficient GPU usage. Alibaba Cloud improved efficiency by implementing a model that processes work based on tokens rather than requests.

The solution speeds up inference processing by splitting it into two phases - prefill and decoding - and handling each in separate GPU pools.

If commercialized, this optimization would likely reduce AI inference server costs and potentially increase demand for non-GPGPU server semiconductors and specialized processing elements (SPE).

This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

Latest comments

Risk Disclosure: Trading in financial instruments and/or cryptocurrencies involves high risks including the risk of losing some, or all, of your investment amount, and may not be suitable for all investors. Prices of cryptocurrencies are extremely volatile and may be affected by external factors such as financial, regulatory or political events. Trading on margin increases the financial risks.
Before deciding to trade in financial instrument or cryptocurrencies you should be fully informed of the risks and costs associated with trading the financial markets, carefully consider your investment objectives, level of experience, and risk appetite, and seek professional advice where needed.
Fusion Media would like to remind you that the data contained in this website is not necessarily real-time nor accurate. The data and prices on the website are not necessarily provided by any market or exchange, but may be provided by market makers, and so prices may not be accurate and may differ from the actual price at any given market, meaning prices are indicative and not appropriate for trading purposes. Fusion Media and any provider of the data contained in this website will not accept liability for any loss or damage as a result of your trading, or your reliance on the information contained within this website.
It is prohibited to use, store, reproduce, display, modify, transmit or distribute the data contained in this website without the explicit prior written permission of Fusion Media and/or the data provider. All intellectual property rights are reserved by the providers and/or the exchange providing the data contained in this website.
Fusion Media may be compensated by the advertisers that appear on the website, based on your interaction with the advertisements or advertisers
© 2007-2025 - Fusion Media Limited. All Rights Reserved.