DX-M1
efficient, and universal at the edge
Overview
The DX-M1 AI chip is more than silicon, it is the declaration that intelligence belongs everywhere, not just in the cloud. At only 2–5W, it delivers the force of 200 GPU-class TOPS, transforming the edge from a passive receiver into an active decision-maker. at just 2-5W through breakthrough efficiency design.
Through its innovative memory design, DX-M1 allows multiple AI models to work side by side, not as a luxury but as a new standard. What once demanded costly, power-hungry systems is now within reach of every device, every factory, every city.
This is not a step forward in chips. It is a step forward in civilization, where real-time intelligence becomes universal, affordable, and inevitable.
Features | Details |
|---|---|
Processor | 25 TOPS |
Signal Interface | PCIe GEN3 x4 / Band width: 4GB/s
(*Compatible to PCIE x1) |
Power | 2W min., 5W max. for DEEPX supported AI models |
Operating Temperature | -25 ~ 85°C (Throttling), -25 ~ 65°C (Non_Throttling) |
Software and Framework Support | Windows 11, 10 64 bit |
Ubuntu 22.04, 20.04 LTS
Support Yocto Project | |
Support TensorFlow, ONNX, Keras, PyTorch by Dataflow complier converted | |
System Support | x86, ARM Based Architecture |
Key Benefits
Superior Thermal ManagementMaintains high performance while staying safely within industrial temperature range (-25°C to 85°C), making it uniquely suitable for real-world applications where competing solutions fail due to overheating.
GPU-Level AI AccuracyAchieves GPU-level AI accuracy using quantized Int-8 precision instead of power-hungry FP32, ensuring reliable on-device intelligence that meets industry standards of less than 1% accuracy drop.
Exceptional Performance EfficiencyDelivers around 20x power performance efficiency compared to GPGPUs and outperforms competitors by more than 2x, ensuring on-device systems can maintain high-level AI capabilities without compromise.
Industry-Leading TCOEven if competitors offered their chips for free, the DX-M1 would still be more economical. Lower power consumption translates to dramatically reduced operational costs, making advanced AI economically feasible at scale.
Performance
- DEEPX DX-M1 (INT8, Batch=1)
- Company A (INT8, Batch=1)
- Nvidia Xavier (INT8, Batch=1)
- This graph shows the benchmark results for Batch=1, all tested under the same conditions.
- Xavier measurements were conducted at room temperature on an NVIDIA Jetson AGX Xavier development kit. The benchmarks utilized INT8 precision with the "no batch" (default=1) option, as recommended by NVIDIA.
- Company A results used the optimize option of "random-calib-set" with default values for the parser and compiler.
- DEEPX DX-M1 numbers are based on the SDK (September 2025), DX-Compiler v.2.0.0, and DX-RT v.3.0.0.
- Company A and DX-M1 were measured at room temperature on a single device through a PCIe interface on an x86 Host PC (Intel® Core™ i7-14700K CPU @ 5.6GHz).
Related Products
DX-M Series
AI Chips
DX-M Series
AI Modules
DX-M Series
Single Board Computers
DX-M Series
SoM Boards
DX-M Series
AI Gateway
DX-M Series
Industrial PCs
Use Cases
Unmatched AI Performance
DX-M1 outperforms 40W GPGPU by 240%, provides 20x efficiency improvement, and comsumes only 5W
Smart Mobility
Autonomous navigation and collision avoidance without network dependency, ensuring reliable operation regardless of connectivity conditions
Smart Factory
On-site quality control and defect detection with superior thermal efficiency, operating reliably in harsh industrial environments without cooling systems
Smart Cities
Live traffic management and crowd monitoring with reduced bandwidth costs, processing thousands of camera feeds locally
Robotics
Extended battery life and compact form factor enable longer autonomous missions with complex AI processing for mobile robots
Drones
Lightweight, power-efficient AI processing for aerial surveillance and autonomous flight control without draining battery life
Edge Computing
High-performance AI inference at network edge with minimal power consumption, reducing server loads and network bandwidth requirements
Smart Homes
Local video analytics and scene recognition without sending personal data to cloud servers, ensuring family privacy
Smart Retail
Real-time customer analytics and inventory management through local video processing, protecting customer privacy while optimizing operations