A unified measurement pipeline on 27 LLM checkpoints shows activation maxima spanning four orders of magnitude, with MoE models 14-23x lower than matched dense models and residual streams carrying the global max in most cases.
GPTQ: Accurate post-training quantization for generative pre-trained transformers
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FairyFuse enables multiplication-free ternary LLM inference on CPUs via fused AVX-512 kernels, achieving 29.6x kernel speedup and 32.4 tokens/s on Xeon with near-lossless quality.
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Measuring Maximum Activations in Open Large Language Models
A unified measurement pipeline on 27 LLM checkpoints shows activation maxima spanning four orders of magnitude, with MoE models 14-23x lower than matched dense models and residual streams carrying the global max in most cases.
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FairyFuse: Multiplication-Free LLM Inference on CPUs via Fused Ternary Kernels
FairyFuse enables multiplication-free ternary LLM inference on CPUs via fused AVX-512 kernels, achieving 29.6x kernel speedup and 32.4 tokens/s on Xeon with near-lossless quality.