Robotics EDA

Robotics Distillation & Weight Transfer Benchmark Explorer

Context: CNBC report on Chinese humanoid robotics models challenging OpenAI distillation assertions
Distillation Controls v2.4 Engine
Distillation Physics: Compress 120B humanoid teacher foundation weights into compact edge models for sub-25ms real-time sensorimotor torque loops.
7.0B
2.2
450B
12%
Distillation Ledger
Initializing edge distillation simulation engine... Teacher foundation: OpenAI Omni-Robot 120B (fp16, 240GB) Target architecture: Humanoid High-DoF Bi-manual Actuator Loop
Evaluated Edge Telemetry OPTIMAL_FRONTIER
Effective Parameters
7.0B
Compression Factor
17.1x
Action Retention Score
94.2%
Latency Delta (vs Teacher)
-82.4%
Distilled Pareto Frontier (Retention vs Latency)
Current Operating Point
Teacher Model (120B Omni)
Inference Latency
18.5 ms
Distillation Ratio
0.058
Edge VRAM Footprint
14.0 GB
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