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nemotron

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Context-Engineering-for-Multi-Agent-Systems

Save thousands of lines of code by building universal, domain-agnostic Multi-Agent Systems (MAS) through high-level semantic orchestration. This repository provides a production-ready blueprint for the Agentic Era, allowing you to replace rigid, hard-coded workflows with a dynamic transparent Context Engine that provides 100% transparency.

  • Updated Aug 17, 2026
  • Jupyter Notebook

Reproducible on-device LLM benchmarks for Apple Silicon (iPhone 17 Pro, M4 Max): Apple Core AI vs MLX vs llama.cpp vs Core ML, same model, same harness — e.g. Qwen3-0.6B decode 181 tok/s (Core AI GPU) vs 112 (MLX) on iPhone 17 Pro; hybrid Mamba-2 models (Nemotron-3 Nano, Granite-4.0-H) included.

  • Updated Sep 4, 2026
  • Python

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