Custom SIMD kernels for ternary LLMs deliver 9.2x faster time-to-first-token, 52x higher throughput, and 14x memory reduction versus standard PyTorch on Apple Silicon and similar CPUs.
SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
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Litespark Inference on Consumer CPUs: Custom SIMD Kernels for Ternary Neural Networks
Custom SIMD kernels for ternary LLMs deliver 9.2x faster time-to-first-token, 52x higher throughput, and 14x memory reduction versus standard PyTorch on Apple Silicon and similar CPUs.