RVA23-compliant K3 Pico-ITX SBC and K3-CoM260 SoM feature SpacemiT K3 octa-core RISC-V AI SoC, up to 32GB RAM, 256GB UFS
SpacemiT has now officially launched the K3 Pico-ITX SBC and K3-CoM260 system-on-module with the RVA23-compliant, SpacemiT K3 octa-core X100 CPU with up
Condensed by AI-Portable from Editorial queue.
SpacemiT has now officially launched the K3 Pico-ITX SBC and K3-CoM260 system-on-module with the RVA23-compliant, SpacemiT K3 octa-core X100 CPU with up to 60 TOPS of AI performance, up to 32GB LPDDR5, 256GB UFS, and PCIe Gen3 x4 NVMe SSD support.
The board also features an eDP connector, a 10GbE SFP+ cage, a Gigabit Ethernet RJ45 port, built-in WiFi 6 and Bluetooth 5.2 wireless connectivity, two USB Type-C connectors, four USB 2.0 ports, an M.2 Key-B socket coupled with a NanoSIM card slot for 4G LTE or 5G cellular connectivity, and more.
System-on-Module – K3-CoM260 SoC – SpacemiT K3 CPU 8x 64-bit RISC-V X100 “big” cores clocked up to 2.4 GHz, RVA23 compliance; 130 KDMIPS performance ( similar to RK3588 ) 8x RISC-V A100 AI Cores with support for up to 1024-bit RVV1.0 parallel computing, optimized for matrix operations. GPU – Imagination Technologies BXM4-64-MC1 GPU with Vulkan 1.3, OpenCL 3.0, and OpenGL ES 1.1/2.0/3.2 support VPU Video decoder – H.265, H.264, VP9 up to 4K @ 120 FPS Video encoder – H.265, H.264 up to 4K @ 60 FPS AI – Up to 60 TOPS (INT4) of AI performance using dedicated TCM and DMA acceleration channels; System Memory – 8GB, 16GB, or 32GB LPDDR5 @ 6400 MT/s (51GB/s bandwidth) Storage 128GB or 256GB UFS 2.2 storage SPI NOR flash MicroSD card slot (yes, on the module) Host interface – 260-pin SO-DIMM edge connector
SoC – SpacemiT K3 CPU 8x 64-bit RISC-V X100 “big” cores clocked up to 2.4 GHz, RVA23 compliance; 130 KDMIPS performance ( similar to RK3588 ) 8x RISC-V A100 AI Cores with support for up to 1024-bit RVV1.0 parallel computing, optimized for matrix operations. GPU – Imagination Technologies BXM4-64-MC1 GPU with Vulkan 1.3, OpenCL 3.0, and OpenGL ES 1.1/2.0/3.2 support VPU Video decoder – H.265, H.264, VP9 up to 4K @ 120 FPS Video encoder – H.265, H.264 up to 4K @ 60 FPS AI – Up to 60 TOPS (INT4) of AI performance using dedicated TCM and DMA acceleration channels;
CPU 8x 64-bit RISC-V X100 “big” cores clocked up to 2.4 GHz, RVA23 compliance; 130 KDMIPS performance ( similar to RK3588 ) 8x RISC-V A100 AI Cores with support for up to 1024-bit RVV1.0 parallel computing, optimized for matrix operations.
The portable AI angle here is not just that Editorial queue published a new item. It is that this material changes how readers should think about portable ai systems in practical terms: what shifts on-device, what still depends on platform or cloud layers, and what kind of user workflow becomes more or less realistic as a result.
From an editorial standpoint, the most useful question is whether this review candidate produces a real behavioral or product constraint change. If the answer is yes, it belongs in AI-Portable because it tells us something about interface friction, local capability, deployment readiness, or the specific work conditions where portable AI may actually land first.
This matters because it touches portable ai through a review candidate signal, which affects real device-side constraints, deployment timing, or product readiness.
Even when the source is directionally useful, the editorial job is to separate confirmed facts from launch framing. Availability, sustained usage evidence, implementation complexity, privacy implications, and integration cost often determine whether a portable AI signal is operationally meaningful or just momentarily interesting.