Products
Structured profiles of edge AI hardware, software and tooling. Every entry links to the manufacturer's own page so figures can be confirmed at source.
Showing 41 of 41 products
Entry-level Jetson developer kit rated at up to 67 INT8 TOPS for compact robots, cameras and vision gateways.
Flagship Orin-generation module rated at up to 275 INT8 TOPS with 64 GB of memory for multi-sensor autonomous machines.
Blackwell-generation robotics module rated at up to 2,070 FP4 TFLOPS with 128 GB of memory.
Discrete 26 TOPS INT8 inference processor supplied as a chip or M.2 module to add vision analytics to an existing system.
Generative-capable M.2 accelerator rated at 40 INT4 TOPS with its own LPDDR4 memory and 2.5 W typical power.
Low-power 4 TOPS Edge TPU module rated at 2 TOPS per watt for small, always-on inference workloads.
Embedded vision SoC with an 8 TOPS deep learning accelerator, dual Cortex-A72 cores and a hardware imaging pipeline.
Eight-core application processor with a 6 TOPS INT8 NPU and 8K video encode and decode, widely used in edge video devices.
Client processor platform with an NPU rated up to 48 TOPS alongside an Intel Arc Xe2 GPU and hybrid CPU cores.
Arm-based 4 nm PC platform with twelve Oryon CPU cores, Adreno graphics and a Hexagon NPU for on-device AI.
Sixteen-core Zen 5 processor with an XDNA 2 NPU rated above 50 TOPS and up to 128 GB of unified memory.
Desktop AI system built on the GB10 Grace Blackwell Superchip with 128 GB of unified memory in a 150 mm chassis.
Dual-socket workstation supporting up to 128 CPU cores and four NVIDIA RTX 6000 Ada GPUs for local model work.
Modular industrial edge system for 12th to 14th Gen Intel Core processors with 9–36 VDC input and wide-temperature operation.
Fanless Jetson AGX Orin inference platform with four Power over Ethernet ports for up to eight cameras.
Fanless Jetson AGX Orin system with 10 gigabit Ethernet, wide 9–36 VDC input and -25 °C to 55 °C operation.
DIN-rail industrial PC and Industrial Edge device with Intel Xeon W processing and 24 VDC industrial power supply.
Industrial edge computer built on Intel Core Ultra with expansion for Hailo accelerators or NVIDIA graphics cards.
Short-depth two-socket 2U server purpose-built for edge sites running video analytics and inference.
2.5U edge box server with a single Xeon Scalable socket, up to 2 TB DDR5 and three full-height PCIe 5.0 x16 slots.
EPYC 8004 edge server supporting up to 64 cores, 768 GB of TruDDR5 memory and up to six single-wide accelerators.
4U AMD EPYC 7003 edge AI system taking up to four single-slot GPUs with a 1200 W ATX 3.0 power supply.
Quad HD camera that fuses deep-learning object classification with 61 GHz radar data on the device.
4K box camera with an on-board NPU for object and licence plate recognition and 120 dB wide dynamic range.
Open-source vision model family covering detection, segmentation, classification, pose and oriented boxes.
GPU-accelerated SDK for building real-time video analytics pipelines on Jetson and x86 GPUs.
Open-source inference package and server that turns a computer or edge device into a vision deployment target.
Official Jetson software stack combining the Linux board support package with CUDA-accelerated AI libraries.
Inference compiler and runtime family that optimises models for NVIDIA GPUs, including Jetson.
Apache 2.0 licensed toolkit for optimising and deploying inference across Intel CPUs, GPUs and NPUs.
MIT-licensed cross-platform inference accelerator with hardware-specific execution providers.
Compiler that maps trained models onto Hailo accelerators, part of the Hailo AI Software Suite.
Edge MLOps platform for building and deploying models to microcontrollers, NPUs, CPUs and GPUs.
MIT-licensed runtime for pulling and serving open-weight models locally through a CLI and local API.
MIT-licensed C and C++ inference engine for open-weight language models, on CPU or GPU backends.
Apache 2.0 on-device runtime for machine learning and generative AI, the successor to TensorFlow Lite.
Apache 2.0 licensed 24-billion-parameter model built for low latency and self-hosted deployment.
MIT-licensed 14-billion-parameter small language model built for low-latency reasoning tasks.
Apache 2.0 compact vision-language model family, from 2 billion parameters down to a 256 million variant.
Apache 2.0 lightweight CNCF-conformant Kubernetes distribution shipped as a single binary under 100 MB.
Container-based fleet platform with over-the-air updates and support for more than 80 device types.
Specifications are summarised from publicly published manufacturer material and are provided for orientation only. Always confirm current figures directly with the manufacturer before purchasing or designing in.