0.3B Student Model Runs Edge Depth Estimation
thetripathi58 · x · 2026-07-08
The post states that after being distilled into a 0.3B student model, the architecture achieves a depth estimation RMSE of 0.310. At one-third the size of NVIDIA's 1B AM-RADIO, it still outperforms the latter.
The author points out that this enables the model to run directly on edge devices with lower latency.
Related event: Ant Robbyant Open-Sources LingBot Vision Models, Topping Depth Benchmarks(18 posts)→
More from Embodied
- Nothing phone mockup turns a film joke into a modular design meme — ZeYanjie · 2026-07-22
- Lightwheel AI Launches SimReadyGen: Text-to-Physics-Accurate Robot Sim Assets — ZeYanjie · 2026-07-22
- Humanoid robot sorting packages in a warehouse sparks debate over job loss — MonaJalal_ · 2026-07-22
- NVIDIA pushes OpenUSD as the common layer for simulation and physical AI — MonaJalal_ · 2026-07-22
- A quadruped robot gets a custom glow-up with a new shell and screen — DynamicWebPaige · 2026-07-22
- A VR teleop demo for an SO-101 arm gets absurdly low latency by using one Python script — MoonL88537 · 2026-07-22