Nature

Speed up integer-arithmetic-only inference via bit-shifting

Quantization is a widely adopted technique in model deployment as it offers a favorable trade-off between computational overhead and performance loss. Integer-arithmetic-only quantization is an ...

Nota AI Has Two MoE Quantization Papers Accepted at ICML 2026 Workshop, Demonstrating Global Competitiveness in Large-Scale AI Optimization

Nota AI, a company specializing in AI model compression and optimization, announced that two of its papers on MoE-specific ...
Semiconductor Engineering

Neural Network Model Quantization On Mobile

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...
Nature

Neural network compression for reinforcement learning tasks

In real applications of Reinforcement Learning (RL), such as robotics, low latency, energy-efficient and high-throughput inference is very desired. The use of sparsity and pruning for optimizing ...
InfoWorld

What is model quantization? Smaller, faster LLMs

Reducing the precision of model weights can make deep neural networks run faster in less GPU memory, while preserving model accuracy. If ever there were a salient example of a counter-intuitive ...

The latest Gemma 4 models use a training trick to slash their on-device memory footprint

You can now download Gemma 4 models with quantization-aware training to reduce the amount of mobile memory required to 1GB.