Content:

• Introduction
• Raspberry Pi Board Comparison (2012–2024)
• Key Takeaways
• What Can You Do With a Pi 5 in 2024?
• Limitations & Workarounds
• Future of Raspberry Pi
• Final Verdict
• Further Reading

Introduction:

Raspberry Pi launched with the goal of reproducing the BBC Micro experience in the modern age. The BBC Micro, released in 1981, introduced Britain’s schoolchildren to the world of microcomputers and accomplished the British government’s goal of increasing computer literacy.

When Eben Upton began designing the first Raspberry Pi prototypes in 2006, there wasn’t a modern equivalent of the BBC Micro. Classrooms may have had computers, but they were expensive and didn’t capture students’ imaginations in the same way as the BBC Micro.

The first production Raspberry Pi single-board computer hit the market in 2012 and was an immediate success. It was affordable, compact, and useful for education. It also quickly became popular with makers and hackers. Since then, many other Raspberry Pi models have come and gone.

The Raspberry Pi has transformed from a humble educational tool into a powerhouse for makers, developers, and AI enthusiasts. Below, we compare every major Pi model from the original (2012) to the latest Pi 5 (2023), highlighting performance, features, and ideal use cases.

Raspberry Pi Board Comparison (2012–2024)

Key Takeaways:

✅ Performance Leap:

• Pi 5 is 2–3× faster than Pi 4 (A76 cores, higher clock).

• 8GB RAM enables lightweight AI models (Llama 2-7B, TinyML).

✅ Connectivity Upgrades:

• Pi 4 introduced USB 3.0 (faster storage).

• Pi 5 added PCIe 2.0 (for NVMe SSDs).

✅ AI Readiness:

• Pi 5’s GPU (VideoCore VII) supports OpenCL/Vulkan (limited ML acceleration).

• Best with USB TPUs (Coral AI, Hailo-8).

What Can You Do With a Pi 5 in 2024?

1. AI & Machine Learning

• Real-time object detection (YOLOv8, TensorFlow Lite).

• Local LLMs (4-bit quantized Mistral/Llama 2).

• Voice assistants (Mycroft, Whisper.cpp).

2. Home Automation & Edge Computing

• Matter/Home Assistant hub (with Zigbee dongle).

• Self-hosted NAS (Pi 5 + NVMe SSD).

3. Retro Gaming & Media

• PS2/GameCube emulation (via Lakka).

• 4K HDR media center (Kodi, Jellyfin).

Limitations & Workarounds

Future of Raspberry Pi

Pi 6 (2025?) – Rumored ARM Cortex-X cores + NPU.

• The Pi 6 is rumored to be a significant upgrade over the Pi 5 (2023), possibly featuring:

• NPU (Neural Processing Unit) – Dedicated AI accelerator for real-time ML tasks (object detection, voice AI, etc.).

• GPU: Vulkan 1.3+ support for better gaming & multimedia.

• RAM: Up to 16GB LPDDR5 (for lightweight server/desktop use).

• Connectivity: Wi-Fi 7 / Bluetooth 5.4, PCIe 2.0 x1 (or better) for faster storage/NVMe.

• USB4 / Thunderbolt? (Unlikely due to cost, but USB 3.2 Gen 2×2 is possible).

• 5G/LTE modem option? (For IoT/edge computing).

Why an NPU?

• AI is becoming essential for robotics, smart cameras, and voice assistants.

• Competitors (like NVIDIA Jetson Orin Nano) already include AI accelerators.

• Could enable local ChatGPT-like models (e.g., LLaMA 3 8B) to run efficiently.

RISC-V Pi – A Cost-Effective, Open-Source Alternative?

RISC-V is an open-source CPU architecture gaining traction as an alternative to ARM. A RISC-V Pi could:

• Lower costs (no ARM licensing fees).

• Better for education & tinkering (fully open ISA).

• Performance? Likely weaker than ARM at first (comparable to early Pi Zero?).

• Use cases:

  • Basic IoT devices (sensors, controllers).

  • Learning CPU architecture (universities, hobbyists).

  • Custom silicon experiments (like Arduino with RISC-V).

Challenges for RISC-V Pi:

• Software support (Linux distros are improving, but ARM is still dominant).

• GPU & multimedia acceleration (RISC-V lacks mature GPU designs).

• Not a Pi 6 competitor—more of a low-cost, experimental board.

Final Verdict

Pro Tip: For serious AI workloads, pair a Pi 5 with a Coral TPU.

Further Reading

• Raspberry Pi AI Kit

• TensorFlow Lite on Pi