AI Performance
48 TOPS INT8 / 12 TOPS FP16:
Handle complex neural models effortlessly, from object detection to segmentation.
Run YOLO, ResNet, MobileNet (90+Models):
Optimized for high throughput and low latency.
Inference Speed:
The Benchmark for Edge AI
Luxonis devices deliver unparalleled AI performance at the edge, combining neural inference, stereo depth, and real-time vision in one compact package.
AI Performance
Why Edge Inference Matters
AI Where It’s Needed
Centralized Local Compute
Luxonis Edge Inference
Reduced Cloud Dependency
Minimized Central Compute Load
Avoid bottlenecks in edge networks that rely on centralized inference.
Uninterrupted Operation
Optimized Latency and Real-Time Response
Energy Efficiency
Scalability
Protecting Privacy at the Edge
In today’s world, safeguarding personal and sensitive data is critical. Luxonis devices are built with privacy in mind, ensuring that Personally Identifiable Information (PII) never leaves the device unless explicitly intended. By processing data locally, our devices help you stay compliant with stringent privacy regulations, including GDPR and CCPA.
Process data locally, anonymize PII, and ensure compliance with privacy regulations like GDPR and CCPA.
On-Device Processing
All data is processed directly on the device, reducing the need to transmit sensitive information to external servers.
PII Protection
Compliance-First Design
Technical Features for Developers
Engineered for
Maximum Flexibility
Subpixel Stereo Depth
High-accuracy depth mapping with up to 1/32 subpixel precision.
Neural Model Optimization
Runs INT8/FP16 models optimized for edge devices, enabling high throughput with low power consumption.
Supports TensorFlow, PyTorch, ONNX, and other model formats.
Parallel Processing
Simultaneously processes stereo depth, object detection, and multiple parallel video streams without external compute.
Power Efficiency
Operates at 5-25W
Eliminates the need for additional cooling or high-wattage power supplies.
Full Configurability
Fine-tune performance and precision settings directly via DepthAI API.
Edge vs. Centralized AI
A Smarter,
Decentralized Approach
Feature | Traditional (Central Compute) | Luxonis Edge Inference |
Latency | High (network-dependent) | Low (on-device) |
Bandwidth Use | High (data streamed to/from cloud or central processing) | Minimal (local processing) |
Energy Efficiency | High system-wide power consumption | Optimized for local efficiency |
Privacy | Data streamed externally | Data processed locally |
Reliability | Dependent on network/cloud availability | Independent, continuous operation |
