Grok-3+: A Scalable, Safe, and Energy-Optimized Architecture for Foundation Model Deployment Across Robotics and Edge Systems.

Grok‑3+ is a next‑generation, deployment‑first large‑language‑model architecture that unifies entropy‑aware sparse Mixture‑of‑Experts routing, hybrid‑precision inference, and inline formal verification to deliver dramatic improvements in latency, energy efficiency, safety, and multi‑agent coordination. We evaluate Grok‑3+ across heterogeneous hardware (Jetson Orin, A100, H100, TPU v5e) and diverse tasks (language understanding, code generation, robotics planning, long‑context QA), demonstrating up to 2× throughput gains and 50–70% energy savings under stringent safety constraints. Through real‑world pilots on TeslaBot and simulation studies, we show that Grok‑3+ reduces unsafe action rates by 20× and extends context windows to 128 k tokens with minimal accuracy loss.

Key Features

• Adaptive Expert Routing (AER): Dynamic, attention‑modulated Top‑2 expert selection for optimal compute utilization.

• Hybrid Precision Inference (HPI): Shannon‑entropy‑driven switching between FP8 and BF16 to balance accuracy vs. efficiency.

• Inline Symbolic Verification (ISV): Z3‑based SMT checks integrated into beam search to enforce safety constraints in real time.

• Role‑Aware Memory (RMM): Efficient recurrent state management for multi‑agent collaboration.

• Energy‑Aware Scheduling: Intelligent workload placement across cloud and edge devices.

Repository & Code
All code, configuration files, and auxiliary scripts are available on GitHub:
https://github.com/akaafridi/grok‑3‑plus

License & Rights
All Rights Reserved. Any reuse or redistribution requires express permission from the author.

Citation

Afridi, M. I. (2025). Grok‑3+ — A Scalable, Safe, and Energy‑Optimized LLM Architecture. Zenodo. https://doi.org/10.5281/zenodo.15341810

Keywords
LLM deployment, sparse Mixture‑of‑Experts, FP8 quantization, formal verification, edge AI, robotics, energy efficiency.

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Author: Mohd Ibrahim Afridi

Contact: afridiibrahim12@outlook.com

© 2025 Mohd Ibrahim Afridi. All rights reserved. This work is provided for viewing purposes only. No part may be reproduced, distributed, or transmitted in any form without the author's prior written permission.