Ai computing series.

The launch of the Innodisk AI on Dragonwing computing series, developed in collaboration with Qualcomm Technologies has just been announced. The flagship EXMP-Q911 COM-HPC Mini module delivers up to 100 TOPS of AI performance while maintaining low power consumption and wide-temperature reliability from -40°C to 85°C. The Qualcomm Dragonwing™ SoCs also offers longevity support through 2038, ensuring supply stability for long-term industrial deployments. As the first product line within Innodisk’s AI on ARM portfolio, the series opens a new chapter for customers seeking sustainable and scalable ARM-based Edge AI solutions.

“With Innodisk’s new AI on Dragonwing series, we’re making advanced edge intelligence more accessible and scalable for industrial customers,” stated Anand Venkatesan, Senior Director, Product Management and Head of Industrial Processors, Qualcomm Technologies, Inc. “By pairing Qualcomm Dragonwing™ SoCs with Innodisk’s in‑house software and peripherals, OEMs can accelerate development and deploy with the performance, efficiency, and reliability they need—today and over the long term.”

The AI on ARM portfolio marks a key milestone in the collaboration between Innodisk and Qualcomm. The efficient architecture of the Qualcomm Dragonwing™ SoCs delivers exceptional AI inference TOPS within strict thermal and power constraints in edge environments. Combined with Innodisk’s extensive in-house expertise in driver porting and peripheral integration, the AI on ARM line-up elevates the SoC’s capabilities, making it a robust foundation for industrial edge AI deployments. This new line-up also reflects a deep co-development effort from both companies, uniting joint hardware–software engineering and early-stage system design to drive next-generation edge intelligence.

This collaboration centres on the EXMP-Q911 COM-HPC Mini module, powered by the Qualcomm Dragonwing™ IQ-9075 processor featuring an 8-core Kryo Gen 6 CPU and an Adreno 663 GPU, supporting 100 TOPS of AI performance. Based on defined test scenarios , the EXMP-Q911 can achieve up to 10× higher AI inference FPS relative to similar modules.

The EXMP-Q911 integrates 36GB of LPDDR5X memory and 128GB of UFS 3.1 storage, along with a rich set of interfaces, including PCIe Gen4, USB 3.2, dual 2.5GbE LAN, dual DP1.2, MIPI CSI-2, CAN FD, and more, delivering strong connectivity for compact, performance-demanding edge systems.

Beyond hardware, Innodisk strengthens its offering with software tools, including IQ Studio, an open-source developer portal on GitHub that provides BSPs, reference code, benchmark tools, and a dedicated community space for developers. These resources help accelerate prototyping, testing, and system integration. In addition, Innodisk’s cloud-based management platform, iCAP, further enhances remote device and AI model management across distributed edge environments.

Built on the compact COM-HPC Mini form factor under the latest PICMG specification, the EXMP-Q911 offers next-generation expandability beyond COM Express Mini and streamlines OEM integration with faster development cycles. As a deployment-ready module, it can be directly embedded into customers’ self-designed carrier boards for seamless system integration and reduced development effort. For a fully optimised integration experience, the module delivers even greater capability when paired with Innodisk’s carrier boards and pre-validated peripherals, including MIPI and GMSL embedded cameras with fully ported drivers for VLM and computer-vision AI, along with modular M.2 expansion cards for networking, storage, and industrial I/O. This combination provides a ready-made solution for streamlined deployment.

Innodisk and Qualcomm Technologies expect to strengthen their collaboration across reference designs, demo kits, and go-to-market initiatives. The product portfolio will also incorporate Qualcomm’s Dragonwing™ IQX and IQ8 SoCs and future ARM platforms for industrial automation, defect detection, AGV/AMR, smart city applications, and a wide range of vertical markets.

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