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Khadas VIM3
The Khadas VIM3 is a high-performance ARM-based single-board computer featuring the Amlogic S905X3 processor with dual NPU cores, designed for edge AI computing, multimedia applications, and embedded Linux development. Professional developers, IoT engineers, and AI researchers use the VIM3 to prototype machine learning models, build intelligent edge devices, and develop advanced multimedia applications with hardware acceleration. This board solves the critical challenge of deploying computationally intensive AI workloads at the edge while maintaining power efficiency and thermal stability in compact form factors.
Product Overview
The Khadas VIM3 is an industrial-grade single-board computer that combines powerful processing capabilities with dedicated neural processing units for AI acceleration. Built on the Amlogic S905X3 SoC, it features a quad-core ARM Cortex-A73 CPU running at 2.2GHz, coupled with dual NPU cores capable of 5 TOPS (Tera Operations Per Second) of INT8 performance. The architecture includes 4GB of LPDDR4 RAM and 32GB of eMMC storage as standard, enabling simultaneous execution of complex applications and real-time inference tasks. The board integrates Mali-G52 MP4 GPU for graphics acceleration and includes dedicated hardware video encoders/decoders supporting 4K H.265 and H.264 codecs, making it ideal for video surveillance, transcoding, and multimedia processing applications.
What distinguishes the VIM3 from competitors is its dual NPU design specifically optimized for TensorFlow Lite and ONNX model inference, combined with Khadas's commitment to open-source software and extensive documentation. The board features multiple connectivity options including Gigabit Ethernet, dual-band WiFi 6, Bluetooth 5.1, and USB 3.1 ports, enabling seamless integration into networked IoT ecosystems. Thermal management is handled through a passive heatsink design with optional active cooling, allowing sustained performance under heavy computational loads. The VIM3 runs Android, Linux, or custom firmware, providing developers with complete flexibility for application development and deployment.
Key Specifications
| Specification | Details |
| Product Type | ARM Single-Board Computer with Dual NPU |
| Brand | Khadas |
| Origin | Original/Authentic |
| Warranty | 7 days on manufacturing defects |
| Shipping | 1-5 days from Bengaluru |
| Delivery | 7-8 days across India |
| Support | 24/7 via Email and WhatsApp |
| Processor | Amlogic S905X3 Quad-core ARM Cortex-A73 @ 2.2GHz |
| RAM | 4GB LPDDR4 |
| Storage | 32GB eMMC with microSD card slot support up to 256GB |
| NPU Performance | Dual NPU cores, 5 TOPS INT8 AI acceleration |
| GPU | Mali-G52 MP4 with OpenGL ES 3.2 support |
| Connectivity | Gigabit Ethernet, WiFi 6 (802.11ax), Bluetooth 5.1, USB 3.1 |
| Video Codec Support | 4K H.265/H.264 encode/decode, VP9, AV1 decode |
| Operating Systems | Android 9.0, Linux (Ubuntu, Debian), Custom Firmware |
| Power Consumption | 5-15W typical operation |
| Dimensions | 82mm x 48mm x 20mm |
Key Features
- Dual NPU cores delivering 5 TOPS INT8 performance for real-time AI inference without external accelerators or cloud dependency
- Quad-core ARM Cortex-A73 CPU at 2.2GHz with Mali-G52 MP4 GPU enabling parallel processing of compute-intensive tasks and graphics rendering
- Hardware video encoding/decoding supporting 4K H.265 and H.264 codecs, reducing CPU load for multimedia and surveillance applications by up to 70%
- WiFi 6 and Gigabit Ethernet connectivity with dual-band support for low-latency, high-bandwidth IoT and edge computing deployments
- Flexible operating system support including Android 9.0 and Linux distributions, allowing developers to choose optimal environments for their specific applications
- Passive thermal design with optional active cooling, maintaining stable operation at full performance under sustained computational loads
Applications and Use Cases
- Edge AI and Machine Learning: Deploy TensorFlow Lite and ONNX models for real-time object detection, facial recognition, and anomaly detection without cloud latency or bandwidth constraints
- Video Surveillance and Analytics: Build intelligent CCTV systems with on-device video processing, person detection, and behavioral analytics using hardware video codecs for 4K stream processing
- IoT Gateway and Smart Home: Create central hubs for home automation with local AI processing, supporting multiple sensor integrations and protocol translations via WiFi 6 and Ethernet
- Embedded Linux Development: Prototype and develop custom Linux applications, kernel modules, and device drivers with full hardware access and extensive community support
- Multimedia Transcoding: Develop video transcoding servers leveraging hardware H.265/H.264 encoding for efficient streaming platform backend infrastructure
- Robotics and Autonomous Systems: Power vision-based navigation and decision-making systems with real-time neural network inference for autonomous robots and drones
How to Use
To get started with the Khadas VIM3, first flash your chosen operating system (Android or Linux) onto the eMMC storage using the Khadas Burn Tool on Windows, macOS, or Linux. Connect the board to a power source using the included USB-C power adapter (minimum 5V/2A), and establish network connectivity via Ethernet or WiFi 6. Access the board through SSH (Linux) or ADB (Android) using the default credentials provided in Khadas documentation. Install the necessary development tools and SDKs based on your application: for AI projects, install TensorFlow Lite or ONNX Runtime; for multimedia, install FFmpeg with hardware acceleration libraries; for general Linux development, use apt-get package manager.
For AI model deployment, convert your trained models to TensorFlow Lite or ONNX format, then use Khadas's NPU SDK to optimize and quantize models for the dual NPU cores. The VIM3 provides dedicated APIs and sample code for NPU inference, enabling you to achieve 5 TOPS performance with minimal latency. Monitor system resources using standard Linux tools like htop and iotop, and leverage the board's GPIO, I2C, and SPI interfaces for sensor integration. Khadas provides extensive documentation, GitHub repositories with example code, and an active community forum for troubleshooting and optimization guidance.
Frequently Asked Questions
What is the difference between Khadas VIM3 and VIM3L?
The VIM3 features dual NPU cores with 5 TOPS INT8 performance and Mali-G52 MP4 GPU, making it ideal for AI-heavy applications. The VIM3L removes the NPU cores but retains the CPU and GPU, making it more affordable for non-AI applications. Choose VIM3 if you need on-device machine learning inference; choose VIM3L for general computing, multimedia, or IoT gateway applications without AI acceleration requirements.
Can I run TensorFlow and PyTorch models directly on the VIM3 NPU?
The VIM3's NPU cores are optimized for TensorFlow Lite and ONNX Runtime inference, not for training. You must train models in PyTorch or TensorFlow on a desktop/cloud GPU, then convert to TensorFlow Lite or ONNX format, quantize to INT8, and deploy on the VIM3 NPU. Khadas provides conversion tools and documentation for this workflow. PyTorch models require conversion to ONNX before NPU deployment.
What is the maximum power consumption and thermal performance of the VIM3?
The VIM3 typically consumes 5-8W during idle operations and 12-15W under full CPU+GPU+NPU load. Peak power consumption can reach 18W during sustained AI inference tasks. The passive heatsink design maintains junction temperatures below 80°C under typical conditions. For continuous heavy workloads or high ambient temperatures above 35°C, Khadas offers optional active cooling solutions. Thermal throttling activates at 100°C to protect the SoC.
When will I receive my order?
Orders are dispatched within 1-5 business days from our Bengaluru warehouse. Delivery takes 7-8 days to most locations across India.
What is your return and warranty policy?
We offer a 7-day return policy on manufacturing defects only. Contact support within 7 days of receipt for free replacement or full refund. Not applicable for user damage or misuse.
Are bulk discounts available?
Yes, wholesale pricing for orders of 10 or more units. Contact our sales team via WhatsApp or email for a customized bulk quote.
Why Buy from The Engineer Store
- Genuine Products: Sourced directly from authorized distributors with authentication
- Expert Team: Our technical team validates every product before listing
- Fast Shipping: Dispatched within 1-5 days from our Bengaluru warehouse
- Pan-India Delivery: 7-8 days to Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata
- Payment Options: COD, UPI, credit/debit cards, net banking, EMI available
- Technical Support: 24/7 expert guidance via email and WhatsApp
- Returns: 7-day return policy on manufacturing defects only
Buy Khadas VIM3 Online in India
Purchase the Khadas VIM3 online at The Engineer Store, India's trusted source for genuine electronics. We deliver across Bengaluru, Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata, Ahmedabad, Jaipur, and Surat. Get the best price on Khadas VIM3 with fast shipping and expert support.
Our team in Bengaluru is available 24/7 to support your journey from product selection to project completion.
Khadas VIM3
The Khadas VIM3 is a high-performance ARM-based single-board computer featuring the Amlogic S905X3 processor with dual NPU cores, designed for edge AI computing, multimedia applications, and embedded Linux development. Professional developers, IoT engineers, and AI researchers use the VIM3 to prototype machine learning models, build intelligent edge devices, and develop advanced multimedia applications with hardware acceleration. This board solves the critical challenge of deploying computationally intensive AI workloads at the edge while maintaining power efficiency and thermal stability in compact form factors.
Product Overview
The Khadas VIM3 is an industrial-grade single-board computer that combines powerful processing capabilities with dedicated neural processing units for AI acceleration. Built on the Amlogic S905X3 SoC, it features a quad-core ARM Cortex-A73 CPU running at 2.2GHz, coupled with dual NPU cores capable of 5 TOPS (Tera Operations Per Second) of INT8 performance. The architecture includes 4GB of LPDDR4 RAM and 32GB of eMMC storage as standard, enabling simultaneous execution of complex applications and real-time inference tasks. The board integrates Mali-G52 MP4 GPU for graphics acceleration and includes dedicated hardware video encoders/decoders supporting 4K H.265 and H.264 codecs, making it ideal for video surveillance, transcoding, and multimedia processing applications.
What distinguishes the VIM3 from competitors is its dual NPU design specifically optimized for TensorFlow Lite and ONNX model inference, combined with Khadas's commitment to open-source software and extensive documentation. The board features multiple connectivity options including Gigabit Ethernet, dual-band WiFi 6, Bluetooth 5.1, and USB 3.1 ports, enabling seamless integration into networked IoT ecosystems. Thermal management is handled through a passive heatsink design with optional active cooling, allowing sustained performance under heavy computational loads. The VIM3 runs Android, Linux, or custom firmware, providing developers with complete flexibility for application development and deployment.
Key Specifications
| Specification | Details |
| Product Type | ARM Single-Board Computer with Dual NPU |
| Brand | Khadas |
| Origin | Original/Authentic |
| Warranty | 7 days on manufacturing defects |
| Shipping | 1-5 days from Bengaluru |
| Delivery | 7-8 days across India |
| Support | 24/7 via Email and WhatsApp |
| Processor | Amlogic S905X3 Quad-core ARM Cortex-A73 @ 2.2GHz |
| RAM | 4GB LPDDR4 |
| Storage | 32GB eMMC with microSD card slot support up to 256GB |
| NPU Performance | Dual NPU cores, 5 TOPS INT8 AI acceleration |
| GPU | Mali-G52 MP4 with OpenGL ES 3.2 support |
| Connectivity | Gigabit Ethernet, WiFi 6 (802.11ax), Bluetooth 5.1, USB 3.1 |
| Video Codec Support | 4K H.265/H.264 encode/decode, VP9, AV1 decode |
| Operating Systems | Android 9.0, Linux (Ubuntu, Debian), Custom Firmware |
| Power Consumption | 5-15W typical operation |
| Dimensions | 82mm x 48mm x 20mm |
Key Features
- Dual NPU cores delivering 5 TOPS INT8 performance for real-time AI inference without external accelerators or cloud dependency
- Quad-core ARM Cortex-A73 CPU at 2.2GHz with Mali-G52 MP4 GPU enabling parallel processing of compute-intensive tasks and graphics rendering
- Hardware video encoding/decoding supporting 4K H.265 and H.264 codecs, reducing CPU load for multimedia and surveillance applications by up to 70%
- WiFi 6 and Gigabit Ethernet connectivity with dual-band support for low-latency, high-bandwidth IoT and edge computing deployments
- Flexible operating system support including Android 9.0 and Linux distributions, allowing developers to choose optimal environments for their specific applications
- Passive thermal design with optional active cooling, maintaining stable operation at full performance under sustained computational loads
Applications and Use Cases
- Edge AI and Machine Learning: Deploy TensorFlow Lite and ONNX models for real-time object detection, facial recognition, and anomaly detection without cloud latency or bandwidth constraints
- Video Surveillance and Analytics: Build intelligent CCTV systems with on-device video processing, person detection, and behavioral analytics using hardware video codecs for 4K stream processing
- IoT Gateway and Smart Home: Create central hubs for home automation with local AI processing, supporting multiple sensor integrations and protocol translations via WiFi 6 and Ethernet
- Embedded Linux Development: Prototype and develop custom Linux applications, kernel modules, and device drivers with full hardware access and extensive community support
- Multimedia Transcoding: Develop video transcoding servers leveraging hardware H.265/H.264 encoding for efficient streaming platform backend infrastructure
- Robotics and Autonomous Systems: Power vision-based navigation and decision-making systems with real-time neural network inference for autonomous robots and drones
How to Use
To get started with the Khadas VIM3, first flash your chosen operating system (Android or Linux) onto the eMMC storage using the Khadas Burn Tool on Windows, macOS, or Linux. Connect the board to a power source using the included USB-C power adapter (minimum 5V/2A), and establish network connectivity via Ethernet or WiFi 6. Access the board through SSH (Linux) or ADB (Android) using the default credentials provided in Khadas documentation. Install the necessary development tools and SDKs based on your application: for AI projects, install TensorFlow Lite or ONNX Runtime; for multimedia, install FFmpeg with hardware acceleration libraries; for general Linux development, use apt-get package manager.
For AI model deployment, convert your trained models to TensorFlow Lite or ONNX format, then use Khadas's NPU SDK to optimize and quantize models for the dual NPU cores. The VIM3 provides dedicated APIs and sample code for NPU inference, enabling you to achieve 5 TOPS performance with minimal latency. Monitor system resources using standard Linux tools like htop and iotop, and leverage the board's GPIO, I2C, and SPI interfaces for sensor integration. Khadas provides extensive documentation, GitHub repositories with example code, and an active community forum for troubleshooting and optimization guidance.
Frequently Asked Questions
What is the difference between Khadas VIM3 and VIM3L?
The VIM3 features dual NPU cores with 5 TOPS INT8 performance and Mali-G52 MP4 GPU, making it ideal for AI-heavy applications. The VIM3L removes the NPU cores but retains the CPU and GPU, making it more affordable for non-AI applications. Choose VIM3 if you need on-device machine learning inference; choose VIM3L for general computing, multimedia, or IoT gateway applications without AI acceleration requirements.
Can I run TensorFlow and PyTorch models directly on the VIM3 NPU?
The VIM3's NPU cores are optimized for TensorFlow Lite and ONNX Runtime inference, not for training. You must train models in PyTorch or TensorFlow on a desktop/cloud GPU, then convert to TensorFlow Lite or ONNX format, quantize to INT8, and deploy on the VIM3 NPU. Khadas provides conversion tools and documentation for this workflow. PyTorch models require conversion to ONNX before NPU deployment.
What is the maximum power consumption and thermal performance of the VIM3?
The VIM3 typically consumes 5-8W during idle operations and 12-15W under full CPU+GPU+NPU load. Peak power consumption can reach 18W during sustained AI inference tasks. The passive heatsink design maintains junction temperatures below 80°C under typical conditions. For continuous heavy workloads or high ambient temperatures above 35°C, Khadas offers optional active cooling solutions. Thermal throttling activates at 100°C to protect the SoC.
When will I receive my order?
Orders are dispatched within 1-5 business days from our Bengaluru warehouse. Delivery takes 7-8 days to most locations across India.
What is your return and warranty policy?
We offer a 7-day return policy on manufacturing defects only. Contact support within 7 days of receipt for free replacement or full refund. Not applicable for user damage or misuse.
Are bulk discounts available?
Yes, wholesale pricing for orders of 10 or more units. Contact our sales team via WhatsApp or email for a customized bulk quote.
Why Buy from The Engineer Store
- Genuine Products: Sourced directly from authorized distributors with authentication
- Expert Team: Our technical team validates every product before listing
- Fast Shipping: Dispatched within 1-5 days from our Bengaluru warehouse
- Pan-India Delivery: 7-8 days to Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata
- Payment Options: COD, UPI, credit/debit cards, net banking, EMI available
- Technical Support: 24/7 expert guidance via email and WhatsApp
- Returns: 7-day return policy on manufacturing defects only
Buy Khadas VIM3 Online in India
Purchase the Khadas VIM3 online at The Engineer Store, India's trusted source for genuine electronics. We deliver across Bengaluru, Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata, Ahmedabad, Jaipur, and Surat. Get the best price on Khadas VIM3 with fast shipping and expert support.
Our team in Bengaluru is available 24/7 to support your journey from product selection to project completion.