- Out-of-Stock
Advanced carrier board compatible with Raspberry Pi Compute Module 5 (CM5) and Compute Module 4 (CM4), offering support for modules in high-performance and energy-efficient servers. With PoE power supply, rack-mounting capability, and support for up to 20 units in a 1U space, it allows for scaling performance to 80 ARM cores, 160 GB RAM, and 10 TB NVMe storage, meeting needs from IoT projects to advanced cloud systems. BladeTPM-V1-0
The Compute Blade is a professional baseboard designed for use with the Raspberry Pi Compute Module 5 (CM5), Compute Module 4 (CM4), and compatible modules. With support for Power over Ethernet (PoE) and industrial rack mounting, the Compute Blade enables the creation of an efficient, energy-saving, plug-and-play server suitable for both home and professional data centers.

Engineered for 24/7 operation, it offers reliability and high performance. Up to 20 Compute Blades can be installed in a 1U standard 19-inch rack slot, delivering up to 80 ARM cores, 160 GB of RAM, and 10 TB NVMe storage. The Compute Blade TPM version provides additional security features, making it an ideal solution for applications requiring high computing density, from simple projects to advanced cloud systems.
Manufacturer BTC Korporacja sp. z o. o. Lwowska 5 05-120 Legionowo Poland sprzedaz@kamami.pl 22 767 36 20
Responsible person BTC Korporacja sp. z o. o. Lwowska 5 05-120 Legionowo Poland sprzedaz@kamami.pl 22 767 36 20
SoM Raspberry Pi CM4 with the SoC Broadcom BCM2711 SoC (4 x Cortex-A72) running at 1.5 GHz, 1 GB LPDDR4 RAM and 8 GB eMMC. Raspberry Pi CM4001008
SoM Raspberry Pi CM4 Lite with the SoC Broadcom BCM2711 SoC (4 x Cortex-A72) running at 1.5 GHz, 1 GB LPDDR4 RAM and wireless connectivity. Raspberry Pi CM4101000
SoM Raspberry Pi CM4 with the SoC Broadcom BCM2711 SoC (4 x Cortex-A72) running at 1.5 GHz, 2 GB LPDDR4 RAM and 8 GB eMMC. Raspberry Pi CM4002008
Raspberry Pi CM5004032 is a high-performance Compute Module 5, equipped with a quad-core Broadcom BCM2712 processor (4 x Cortex-A76) clocked at 2.4 GHz, 4 GB of LPDDR4 RAM, and 32 GB of built-in eMMC storage. With its strong specifications and ample data storage, this module is perfectly suited for IoT applications, embedded systems, and industrial automation.
No product available!
Raspberry Pi CM5008032 is a high-performance Compute Module 5, equipped with a quad-core Broadcom BCM2712 processor (4 x Cortex-A76) clocked at 2.4 GHz, 8 GB of LPDDR4 RAM, and 32 GB of built-in eMMC storage. This module provides substantial computational power and reliable data storage, making it an ideal choice for advanced IoT applications, embedded systems, and industrial automation.
No product available!
Raspberry Pi CM5016016 is an exceptionally high-performance Compute Module 5, equipped with a quad-core Broadcom BCM2712 processor (4 x Cortex-A76) clocked at 2.4 GHz, 16 GB of LPDDR4 RAM, and 16 GB of built-in eMMC storage. With its combination of high computational power and solid storage, this module is ideal for IoT applications, industrial automation, and embedded systems that require high performance.
No product available!
No product available!
No product available!
No product available!
No product available!
No product available!
No product available!
No product available!
No product available!
Spacer sleeve with internal diameter 3.2mm and external diameter 5mm, sleeve length 8mm. The sleeve is made of white polyamide, Fix & Fasten, RoHS
No product available!
No product available!
No product available!
Module with 16-key keyboard and 6-digit LED display
No product available!
No product available!
No product available!
No product available!
Advanced carrier board compatible with Raspberry Pi Compute Module 5 (CM5) and Compute Module 4 (CM4), offering support for modules in high-performance and energy-efficient servers. With PoE power supply, rack-mounting capability, and support for up to 20 units in a 1U space, it allows for scaling performance to 80 ARM cores, 160 GB RAM, and 10 TB NVMe storage, meeting needs from IoT projects to advanced cloud systems. BladeTPM-V1-0