GMO Internet, NTT East, NTT West, and QTnet Confirm Practical Performance of Remote Distributed AI Infrastructure Between Tokyo and Fukuoka Utilizing IOWN APN, Tailored to Workload Characteristics

GMO Internet, Inc. (Headquarters: Shibuya-ku, Tokyo; President and Representative Director: Masaru Ito; hereinafter referred to as GMO Internet), NTT East Corporation (Headquarters: Shinjuku-ku, Tokyo; President and Representative Director: Naoki Shibuya; hereinafter referred to as NTT East), NTT West Corporation (Headquarters: Osaka-shi, Osaka; President and Representative Director: Ryota Kitamura; hereinafter referred to as NTT West), and QTnet Co., Ltd. (Headquarters: Fukuoka-shi, Fukuoka; President and Representative Director: Yoshio Ogura; hereinafter referred to as QTnet) have completed a technical demonstration of a remote distributed AI infrastructure between Tokyo and Fukuoka utilizing the "APN (All-Photonics Network)" of "IOWN (Innovative Optical and Wireless Network)".

In this demonstration, conducted from November 2025 to February 2026, a live IOWN APN circuit was established between Tokyo (storage) and Fukuoka (GPU). The performance of an AI development platform connecting GPUs and large-capacity storage of "GMO GPU Cloud" was measured and evaluated for AI workloads. As a result, for Large Language Model (LLM) training, a performance degradation of only approximately 0.5% compared to local environments was confirmed, indicating an extremely limited impact. For image classification tasks involving data loading, it was confirmed that practical-level processing is possible even in a remote environment through optimization of training data, etc. This demonstration proved that practical AI development is possible in a remote distributed environment through designs tailored to workload characteristics.

Prior to this demonstration, the four companies conducted a preliminary demonstration (Phase 1) in July 2025, performing performance tests in a pseudo-remote environment simulating the Tokyo-Fukuoka distance (approximately 1,000 km). Details of this preliminary demonstration have been published as a technical report.

Press Release: Technical Demonstration of Next-Generation Distributed AI Infrastructure Utilizing "GMO GPU Cloud" and Low-Latency Circuit "IOWN APN" Commences

Technical Report: Details and Results of GPU/Storage Connection Performance Test in Pseudo-Remote Environment Utilizing "IOWN APN"

Based on the results of this demonstration, the four companies will continue to advance initiatives towards the practical application of remote distributed AI infrastructure that meets customer needs.

Background and Objectives

With the recent proliferation of generative AI and Large Language Models (LLMs), the demand for AI development infrastructure has rapidly expanded. Traditionally, GPUs and large-capacity storage have been required to be physically adjacent. However, to address data center space constraints and the need for companies to manage their data within their own facilities, the realization of distributed AI development infrastructure that transcends geographical limitations has become necessary. The four companies are leveraging IOWN's characteristics of high-speed, high-capacity, and low-latency...