[Project] PentaNet: Pushing beyond BitNet with Native Pentanary {-2, -1, 0, 1, 2} Quantization (124M, zero-multiplier inference)

Reddit - Machine Learning 1 min read

About this article

Hey everyone, I've been experimenting with extreme LLM quantization following the BitNet 1.58b paper. While ternary quantization {-1, 0, 1} is great for replacing costly matrix multiplications with simple additions, I wondered if we were leaving too much model capacity on the table by overly restricting the weights. So, I built and trained PentaNet from scratch — a custom architecture that expands the weight states to pentanary: {-2, -1, 0, +1, +2}. Why ±2? Because multiplying by 2 doesn't re...

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Originally published on March 28, 2026. Curated by AI News.

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