A practical toolkit and step-by-step guide for quantizing ONNX models for Qualcomm® AI Runtime (QAIRT) and deploying them on Qualcomm NPUs. pip install ultralytics ...

We propose a novel post-training quantization method for large language models with learnable parameters, novel loss function and Test-time adaptation scheme. Post-training quantization (PTQ) for ...

On r/LocalLLaMA, where discussions were centered yesterday (5/27) on reports that the Qwen3.6 27B model had reached practical quality, today (5/28) saw a series of empirical reports stating, "I ...

More parameters doesn't always mean more capabilities.

Three AI technology topics are gaining attention on X (Twitter). One is the RTX inference optimization for GoogleGemma 4 31B (up to 2.7x speedup) through a collaboration between NVIDIA and ggerganov.

Your CPU can run a coding AI—here's why you shouldn't pay for one (as long as you have the patience for it).

Abstract: Recent improvements in the accuracy of machine learning (ML) models in the language domain have propelled their use in a multitude of products and services, touching millions of lives daily.

Version 5.0 Modernizes DNN Engine, Adds LLM/VLM Support, and Enhances Core, Hardware Acceleration, and 3D Stack.