In the heart of a neon-lit lab, two rival engineers, Alex and Jordan, prepared for an ultimate battle of embedded AI computing. Their weapons? The RK3588 and the NVIDIA Jetson—two of the most powerful edge AI platforms in existence.
As the clock struck midnight, Alex unveiled the RK3588, a Rockchip-powered beast featuring an 8-core CPU, a 6 TOPS NPU, and Mali-G610 MP4 GPU. Meanwhile, Jordan smirked, knowing their NVIDIA Jetson AGX Orin boasted a 2048-core Ampere GPU, a 12-core Cortex-A78AE CPU, and 275 TOPS AI performance.
Their challenge? To build an AI-powered drone capable of recognizing objects in real-time. The stakes? Bragging rights—and a high-paying research grant.
Round 1: Compute Performance 🖥️
Alex initiated the first test—raw processing. They ran deep-learning benchmarks, pushing both devices to their limits.
| Metric | RK3588 | NVIDIA Jetson AGX Orin |
|---|---|---|
| CPU Performance | 8-core Cortex-A76/A55 | 12-core Cortex-A78AE |
| GPU | Mali-G610 MP4 | 2048-core Ampere GPU |
| AI Performance | 6 TOPS NPU | 275 TOPS Tensor Cores |
Jordan grinned. “Jetson wins hands down!” they declared. Alex, however, had other ideas.
Round 2: Power Efficiency 🔋
A drone must balance power with performance. They measured wattage under AI workloads.
| Scenario | RK3588 Power Draw | NVIDIA Jetson AGX Orin Power Draw |
|---|---|---|
| Idle | ~3W | ~7W |
| Full AI Load | ~10W | ~60W |
Alex smirked. “RK3588 sips power compared to Jetson’s hunger. In edge AI, efficiency matters.” Jordan admitted it was a fair point, but they weren’t conceding yet.
Round 3: AI Processing 🚀
The final test: an AI model for real-time image recognition.
| Task | RK3588 FPS | Jetson AGX Orin FPS |
|---|---|---|
| YOLOv5 Inference | 25 FPS | 180 FPS |
| ResNet50 | 30 FPS | 200 FPS |
Jordan laughed. “Jetson demolishes RK3588 in raw AI power!”
Alex sighed but countered, “But my platform costs one-fifth the price and still gets the job done. Many startups can’t afford Jetson.”
Jordan hesitated. That was true. The RK3588 provided an affordable entry into AI computing, even if it lacked raw power.