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Plug-in on-device USB-type AI accelerator
MLD-R1 AI USB

Turn your device into an AI inference machine

One stick delivers 10 TOPS of on-device AI inference over a USB port. No chassis swap required.

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Powered by the ultra-low-power REGULUS AI SoC

3 W power draw, engineered for 24/7 operation

Accelerate vision to generative AI workload at the edge

Mobilint’s NPU architecture has been validated with over 490 open- and closed-sourced models.

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Product specs

NPU

REGULUS AI SoC

Performance

10 TOPS (INT8)

CPU

Quad-core ARM Cortex-A53, up to 1.2 GHz

TDP

3 W

Memory

4 GB / 8 GB LPDDR4X at 4,266 MT/s

Supported OS

Windows, Linux

Supported Frameworks

Keras, TensorFlow, TensorFlow Lite, PyTorch, ONNX

LED Indicators

1 (Power LED)

Host Architectures

x86, ARM

Ingress Protection

IP65 (TBD)

Data Interface

USB 3.1 Gen1

Dimensions (mm)

90 ✕ 40 ✕ 16

Weight (g)

88

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Speed up model validation and edge prototyping on your existing machine, wherever you are

Run models on portable diagnostic devices without network connectivity.

Ready to evaluate MLD-R1 in your environment?

Request a Product Development Kit or contact our team to discuss your deployment requirements.

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AI Frameworks (via SDK qb)

  • Keras

  • TensorFlow / TensorFlowLite

  • PyTorch

  • ONNX

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Operating Systems*

  • Windows 11

  • Linux 22.04.5

    *To be updated

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Host Architectures

  • x86

  • ARM

  • RISC-V

Keep your existing pipeline

Whether you're deploying a PyTorch model on a Windows laptop or running TensorFlow inference on an ARM-based industrial PC, MLD-R1 connects and runs.

Forklift Safety

Real-time pedestrian detection, hard-hat recognition, collision-prevention alerts.

AGVs and AMRs

Onboard vision and generative AI inference for autonomous mobile robots. Sub-10 W draw compatible with battery-powered operation.

Construction Machinery

Restricted-zone intrusion detection and hazard monitoring on moving equipment at construction sites.

Industrial Safety Monitoring

Worker safety monitoring across plants and logistics centers.

MLX-R1 goes where MLX-R1 fits

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