SOAR improves NVFP4 post-training quantization accuracy for LLMs by analytically solving joint scale optimization and searching decoupled scales.
Batquant: Outlier-resilient mxfp4 quantization via learnable block-wise optimization
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QuantClaw dynamically routes precision in agent workflows to cut cost by up to 21.4% and latency by 15.7% while keeping or improving task performance.
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SOAR: Scale Optimization for Accurate Reconstruction in NVFP4 Quantization
SOAR improves NVFP4 post-training quantization accuracy for LLMs by analytically solving joint scale optimization and searching decoupled scales.
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QuantClaw: Precision Where It Matters for OpenClaw
QuantClaw dynamically routes precision in agent workflows to cut cost by up to 21.4% and latency by 15.7% while keeping or improving task performance.