STMicroelectronics adds DSP and edge-AI hardware to STM32H7P MCUs
STMicroelectronics has unveiled the STM32H7P microcontroller series with dedicated hardware for digital signal processing and neural processing, aimed at industrial control, sensing and edge-AI workloads. The chips are sampling now, with production planned for January 2027 and pricing starting at $4.43 for 10,000-unit orders.
Why it matters: - The STM32H7P gives industrial designers a single MCU platform for real-time control, DSP and edge AI. - STMicroelectronics is targeting applications that need more performance without adding a separate DSP or moving to a higher-cost platform. - The new series is positioned for power electronics, motor control, sensing, condition monitoring and other mission-critical embedded systems.
What happened: - STMicroelectronics introduced the STM32H7P microcontroller series in Geneva on Nov. 4, 2026. - The chips combine a 2773-CoreMark Arm Cortex-M7 with two dedicated accelerators: the Hardware Signal Processor and the Neural-ART Neural Processing Unit. - The STM32H7P series is sampling at OEMs now. - Production is planned for January 2027. - The series starts at $4.43 for a 1MB Flash part in an LQFP100 package, for orders of 10,000 units. - The NUCLEO-H7P5II evaluation board and STM32H7P5IDK Discovery kit will be available in January 2027. - More information is available on STMicroelectronics' STM32H7P page.
The details: - The Hardware Signal Processor is designed for matrix, vector and digital signal processing workloads. - ST says the HSP can cut FFT time by up to 5 times versus software running on the Cortex-M7. - The HSP offloads work from the main CPU and can reduce the need for a dedicated external DSP. - The Cortex-M7 runs at up to 520MHz. - The new MCUs include larger tightly coupled memories for faster access to instructions and data. - ST says the architecture supports faster real-time control, signal processing and AI inference. - The series offers up to 2MB of Flash for code and data storage. - ST says that memory capacity comes at a price point similar to the previous 1MB STM32H7 series. - The STM32H7P includes advanced analog peripherals such as ADCs, DACs and comparators. - The chips also include timers inherited from the STM32G5 mixed-signal series. - The Neural-ART NPU delivers up to 85 GOPS. - ST says the NPU has shown 40-times faster inference on its AI Arc Fault Circuit Interrupter model for solar-inverter safety. - ST says the anomaly detection model runs 20 times faster. - ST says the AI battery-management system model runs 15 times faster. - The STM32H7P works with ST’s Edge AI Suite for embedded machine-learning development. - ST also supports the series with DSP enablement software and X-CUBE-MCSDK-2 motor-control tools. - The chips connect with the upgraded STM32Cube ecosystem, including STM32CubeMX2 and the code-size optimized HAL2. - The MCUs operate up to 125°C ambient temperature. - The series is part of ST’s industrial longevity support program. - An exposed-pad LQFP package is available to improve thermal dissipation.
Between the lines: - ST is broadening the STM32 line from general-purpose embedded control into higher-value industrial AI and signal-processing use cases. - The pricing and memory positioning suggest ST is trying to keep the series accessible for mass-market designs, not just premium industrial systems. - The mix of analog, timer and AI features points to a single-chip approach for power electronics and control applications.
What's next: - OEMs can begin evaluating samples now. - Developers can use the new boards and software stack when hardware becomes available in January 2027. - The launch should expand ST’s industrial ecosystem around STM32Cube, motor control and embedded AI development.
The bottom line: - The STM32H7P is STMicroelectronics’ pitch for a more capable industrial MCU: more AI and DSP acceleration, more memory and more real-time control in one chip.
Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.
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