Jetson Nano vs Raspberry Pi: Choosing the Right SBC for AI at the Edge
The AI Showdown: When “Smart” Isn’t Smart Enough
When makers and startups look for a single-board computer (SBC), the Raspberry Pi often tops the list; affordable, flexible, and supported by a massive community. But what if your next project needs to do more than light up LEDs or stream a camera feed? What if it needs to see, process, and respond intelligently right at the edge?
Enter the NVIDIA Jetson Nano: a compact powerhouse designed specifically for deep learning, real-time video analytics, and embedded AI. Whether you're building smart robots, advanced surveillance systems, or factory automation, Jetson Nano takes you from prototype to production-ready with ease.
Let’s explore why Jetson Nano might be the right upgrade for your next AI-driven idea.
Why to Choose Jetson Nano
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Design Philosophy: AI-First vs General-Purpose
Jetson Nano is built from the ground up for machine learning and computer vision, thanks to its dedicated 128-core Maxwell GPU for hardware-accelerated AI.
Raspberry Pi is a general-purpose SBC, excellent for prototyping, education, and IoT but not optimized for deep learning workloads.
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Spec-by-Spec Comparison
Feature Jetson Nano Raspberry Pi 5 CPU Quad-core Cortex-A57 @ 1.4 GHz Quad-core Cortex-A76 @ up to 1.8 GHz GPU 128-core Maxwell (CUDA support) Video Core VII (no CUDA) RAM 4GB LPDDR4 4GB / 8GB LPDDR4 AI Compute ~472 GFLOPS Limited; 13 TOPS with external AI kit Connectivity 4× USB 3.0, HDMI, DP, Gigabit Ethernet, GPIO, MIPI CSI 2× USB 3.0, 2× USB 2.0, dual micro-HDMI, Wi-Fi 6, Bluetooth 5.0 Power Usage 5–10W (for AI workloads) 3–5W (standard use) -
AI & Deep Learning: Performance Matters
- Jetson Nano can be 22–30× faster than Raspberry Pi for deep learning tasks.
- Example: ResNet-50 achieves ~36 FPS on Jetson Nano vs ~1.4 FPS on Raspberry Pi 3.
- Supports AI frameworks like TensorFlow, PyTorch, OpenCV, with GPU acceleration.
- Ideal for real-time object detection, robotics, video analytics, and AI inferencing.
- Raspberry Pi, without accessories, is suited for basic ML/AI experiments.
- AI accelerators (e.g., Google Coral or Hailo) can improve performance but require additional investment and integration effort.
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Connectivity & Ecosystem
- Raspberry Pi wins in wireless connectivity and modular expansion, built-in Wi-Fi, Bluetooth, and a vast accessory (HAT) ecosystem.
- Jetson Nano lacks built-in wireless but supports multiple high-speed cameras and industrial sensors, making it perfect for professional AI applications.
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Software & Development Tools
- Jetson Nano is powered by the NVIDIA JetPack SDK, which includes:
- Optimized AI libraries: CUDA, cuDNN, TensorRT
- Full support for AI model deployment at the edge
- Raspberry Pi supports a variety of Linux OS options (Raspberry Pi OS, Ubuntu), good for education and Python-based development but not AI-optimized.
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Cost & Value
Raspberry Pi 5 Jetson Nano Starting Price ~$50–$80 ~$99 (Dev Kit) AI Upgrade Cost Adds ~$70 for AI Kit Up to ~$250 for production modules Best For Entry-level projects and education Performance-per-dollar AI/deep learning
- Real-time performance for vision/AI tasks
- Robotics, defect detection, automation
- Simultaneous camera/video processing
- Professional AI model deployment
- Industrial use cases requiring high inference speed
Why Raspberry Pi Makes Sense
- Budget-friendly education projects
- Light IoT applications
- Media centers, smart homes
- Wi-Fi/Bluetooth-enabled solutions
- Rapid prototyping with wide documentation
Limitations to Consider
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Jetson Nano:
- Higher initial cost
- No built-in Wi-Fi/Bluetooth
- Smaller maker community than Raspberry Pi
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Raspberry Pi:
- Not suitable for large AI workloads
- No native GPU acceleration
- May overheat or throttle under heavy tasks
Final Thoughts: AI at the Edge is the Future
If you're aiming to build the next generation of intelligent machines, the Jetson Nano provides the AI horsepower and professional tooling to bring your ideas to life. For simpler projects or educational purposes, Raspberry Pi remains a phenomenal platform.
As edge AI continues its explosive growth expected to reach $66 billion by 2030 both boards have their place. But if you want to build smarter, faster, and more capable systems, Jetson Nano gives you the edge.
Partner With Us
At AI India Innovations, we are building intelligent, scalable, and reliable AI solutions to power the next generation of edge computing in India. Whether you're a robotics startup, smart manufacturing company, AI research lab, or system integrator; we can help you bring AI to life with NVIDIA Jetson and embedded platforms.
Author:
Mr. Tanish Jain (AI Embedded Developer)
Contact us to start your edge AI journey.
Together, let’s shape the future of intelligent machines.