Edge AI hardware: industrial computers, modules and accelerator cards arranged under blue network lighting

The Global Intelligence Platform for Edge AI

Edge AI Starts Here

Explore the processors, devices, software and infrastructure powering real-time artificial intelligence at the edge.

EdgeAI.computer is available for acquisition, licensing or strategic partnership.

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Categories
16
Solutions profiled
41
Companies
30
Network portals
17

Industry categories

Sixteen structured categories covering edge AI silicon, systems, software and applied deployments. Each has its own reference page.

All solutions

Representative platforms across silicon, systems, software and tooling, with the key details engineering and procurement teams shortlist on.

All products
Close-up of a compact edge AI system-on-module with heatsink mounted on a carrier board
NVIDIA

NVIDIA Jetson Orin Nano Super Developer Kit

Entry-level Jetson developer kit rated at up to 67 INT8 TOPS for compact robots, cameras and vision gateways.

AI performance
Up to 67 TOPS (INT8, sparse)
GPU
NVIDIA Ampere, 1,024 CUDA cores, 32 Tensor cores
CPU
6-core Arm Cortex-A78AE
Deployment
Bench development, then embedded into a carrier board or enclosure
Autonomous mobile robots
Multi-stream video analytics
Vision gateways
High-performance edge AI module with large heatsink on an engineering bench
NVIDIA

NVIDIA Jetson AGX Orin 64GB module

Flagship Orin-generation module rated at up to 275 INT8 TOPS with 64 GB of memory for multi-sensor autonomous machines.

AI performance
Up to 275 TOPS (INT8, sparse)
GPU
2,048-core NVIDIA Ampere GPU with 64 Tensor cores
CPU
12-core Arm Cortex-A78AE
Deployment
Robot chassis, autonomous vehicle compute bay or inference appliance
Autonomous machines
Multi-camera sensor fusion
Industrial robotics
Autonomous mobile robot in a warehouse aisle with sensors visible on its chassis
NVIDIA

NVIDIA Jetson Thor T5000 module

Blackwell-generation robotics module rated at up to 2,070 FP4 TFLOPS with 128 GB of memory.

AI performance
Up to 2,070 TFLOPS (FP4)
GPU
NVIDIA Blackwell GPU with transformer engine and MIG support
CPU
14-core Arm Neoverse V3AE
Deployment
Robot compute bay or autonomous machine, on a carrier board
Humanoid and mobile robots
Multi-sensor autonomy
On-robot vision-language models
M.2 format AI accelerator module held above a circuit board
Hailo

Hailo-8 AI accelerator

Discrete 26 TOPS INT8 inference processor supplied as a chip or M.2 module to add vision analytics to an existing system.

AI performance
Up to 26 TOPS (INT8)
Architecture
Integrated neural network core, no external DRAM required
Form factor
Chip, or M.2 M-key / B+M / A+E module
Deployment
Add-in module inside an edge computer, NVR or camera
Retail video analytics
Smart city cameras
Industrial inspection
Compact M.2 AI accelerator module with memory packages visible on the board
Hailo

Hailo-10H AI accelerator

Generative-capable M.2 accelerator rated at 40 INT4 TOPS with its own LPDDR4 memory and 2.5 W typical power.

AI performance
40 TOPS (INT4) / 20 TOPS (INT8)
Memory
4 GB or 8 GB LPDDR4 / LPDDR4X
Typical power
2.5 W
Deployment
M.2 slot in an edge computer, camera or in-vehicle unit
On-device language assistants
Vision-language analytics
Automotive cabin AI
Small machine learning accelerator module beside a coin for scale
Google

Google Coral M.2 Accelerator (Edge TPU)

Low-power 4 TOPS Edge TPU module rated at 2 TOPS per watt for small, always-on inference workloads.

AI performance
4 TOPS (INT8) peak, 2 TOPS per watt
Interface
PCIe Gen2 x1 (M.2) or USB 2.0 / 3.0 (USB Accelerator)
Form factors
M.2 A+E, M.2 B+M, USB, solder-down module 15.0 × 10.0 × 1.5 mm
Deployment
Embedded board, single-board computer or small enclosure
Always-on sensor vision
Compact retail devices
Embedded classification

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.

Chip designers, hardware manufacturers, software providers, robotics and computer-vision companies working across the edge AI stack.

Company directory

NVIDIA

Chip manufacturer

Develops the Jetson family of edge system-on-modules, the DGX Spark desktop AI system and the JetPack, TensorRT and DeepStream software stacks used for edge inference, robotics and vision AI.

Santa Clara, California, United States

Intel

Chip manufacturer

Supplies Core Ultra client processors that combine CPU, Arc graphics and an integrated NPU, and maintains the open-source OpenVINO toolkit for optimising inference on Intel CPUs, GPUs and NPUs.

Santa Clara, California, United States

Qualcomm

Chip manufacturer

Designs the Snapdragon X platform for Windows PCs and edge clients, pairing Oryon CPU cores, Adreno graphics and the Hexagon NPU. Qualcomm also owns the Edge Impulse edge MLOps platform.

San Diego, California, United States

AMD

Chip manufacturer

Produces Ryzen AI processors that combine Zen 5 CPU cores, RDNA 3.5 graphics and the XDNA 2 NPU, with large unified memory configurations used for local generative AI workloads.

Santa Clara, California, United States

Google

Chip manufacturer

Publishes the Coral Edge TPU accelerators for low-power on-device inference and maintains LiteRT, the on-device runtime that succeeded TensorFlow Lite, together with the open-weight Gemma model family.

Mountain View, California, United States

Texas Instruments

Chip manufacturer

Supplies the AM6xA and TDA4 processor families, which combine Arm application cores, vision and imaging accelerators and a deep learning accelerator for embedded vision, robotics and automotive designs.

Dallas, Texas, United States

AI discovery assistant

Find the Right Edge AI Solution

Ask a question in your own words. Answers are drawn only from structured data published on this platform, with links to the relevant product, company and category pages. Where information has not been verified, the assistant says so.

One Connected AI Technology Ecosystem

Together, these 17 platforms create an integrated discovery and commercial network spanning AI PCs, agentic AI, chips, data centres, servers, software, hardware, intelligent devices, accessories, commerce and edge computing.

Explore the network

AIPC.computer

AI PCs

Discovery platform for AI PCs, NPUs and next-generation personal computing.

Available for acquisition, licensing or strategic partnership

AiAgents.computer

Agentic AI

Directory of AI agents, agent frameworks and autonomous software workers.

Available for acquisition, licensing or strategic partnership

Datacenter.computer

Data Centres

Data centre infrastructure, colocation, cooling and AI capacity discovery.

Available for acquisition, licensing or strategic partnership

Servers.computer

Servers

Server platforms, rack systems and enterprise compute discovery.

Available for acquisition, licensing or strategic partnership

Laptops.computer

Laptops

Laptop and mobile workstation discovery across every major manufacturer.

Available for acquisition, licensing or strategic partnership

Semiconductors.computer

Semiconductors

Semiconductor industry intelligence, foundries, fabs and supply chain.

Available for acquisition, licensing or strategic partnership

Frequently asked questions

What is edge AI?
Edge AI runs machine learning inference on or near the device that produces the data — a camera, a robot, a vehicle or an industrial computer — instead of sending everything to a remote data centre.
How do I choose between an edge module, an industrial computer and an edge server?
Match the platform to the physical site and the workload. Modules suit embedded products, industrial computers suit cabinets and factory floors, and edge servers suit rooms where several workloads and multiple video streams are consolidated.
Does EdgeAI.computer publish its own benchmarks?
No. We publish structured summaries drawn from public manufacturer material and link to the source. Where a figure has not been verified, we say so rather than estimating it.
How can a company be listed?
Submit your company through the listing page. Every submission is reviewed editorially before publication and we may contact you to verify details.