Asus showcases next generation AI infrastructure at India AI Impact Summit 2026

India’s AI race is shifting from ideas to infrastructure. At the India AI Impact Summit 2026 in New Delhi, Asus made one thing clear: serious AI ambitions demand serious computing power.

The company unveiled a broad portfolio of artificial intelligence (AI) servers, supercomputing platforms, and edge systems aligned with the goals of the IndiaAI Mission. As AI adoption accelerates across research labs, startups, and enterprises, access to high-performance infrastructure is quickly becoming the real differentiator.

AI supercomputing built for scale

The highlight was the Asus AI POD powered by NVIDIA Grace Blackwell Ultra NVL72. This system integrates NVIDIA Grace CPUs with Blackwell GPUs and is designed for large language model training and inference at extreme scale. Such platforms are typically used in advanced research, national AI initiatives, and large enterprise deployments where model sizes and datasets are massive.

Asus also showcased infrastructure built around NVIDIA Vera Rubin NVL72, combining 72 GPUs, 36 CPUs, NVLink 6 switches, ConnectX-9 networking, and BlueField-4 data processing units. These configurations are intended for high-performance computing (HPC), scientific simulations, and advanced AI model development.

For institutions participating in IndiaAI Mission projects, this level of compute density can significantly reduce model training time, improve experimentation cycles, and support more complex workloads.

Enterprise servers ready for AI workloads

Beyond supercomputing clusters, Asus presented systems tailored for enterprise AI environments.

The RS720-E12, a 2U dual-socket server powered by Intel Xeon 6 Scalable processors, supports PCIe Gen5 expansion and DDR5 memory. It is suited for AI training, virtualization, analytics, and data-intensive enterprise tasks.

Meanwhile, the XA AM3A-E13 runs on eight AMD Instinct MI355X GPUs with dual AMD EPYC 9005 processors. With support for low-precision data formats such as FP4 and FP6 and up to 288 GB of high-bandwidth memory, the platform targets generative AI and high-throughput inference workloads.

For organizations building in-house AI capabilities, these systems offer scalable foundations without immediately moving to national-scale supercomputing clusters.

From desktop AI to edge intelligence

Interestingly, Asus also addressed developers and edge deployments. The Ascent GX10, a compact desktop AI supercomputer powered by the NVIDIA GB10 Grace Blackwell Superchip, delivers up to 1 petaFLOP of AI performance. With 128 GB memory supporting model fine-tuning up to 200 billion parameters, it is positioned for research labs and advanced AI developers.

On the edge side, the PE1100N enables real-time inference in industrial and outdoor environments. By processing data locally, it reduces latency and minimizes back-and-forth data transfer to centralized data centers. Use cases include smart cities, manufacturing automation, and retail analytics.

Why this matters for India’s AI roadmap

India’s AI vision depends on compute access as much as talent. By covering everything from edge devices to AI supercomputing clusters, Asus is targeting every layer of the AI stack.

If IndiaAI Mission initiatives are to move from policy to production, infrastructure like this will be a central piece of the puzzle.

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