PyTorch(@PyTorch):Use PyTorch-native libraries within the NVIDIA NeMo Framework to customize models to hit your exacting requirements for latency, speed, memory, and compute. @NVIDIA's blog demonstrates how quantization-aware distillation (QAD) improves the Nemotron 3.5 Lightning model using NVIDIA Model Optimizer. We walk through the entire training pipeline, and show how QAD consistently outperforms post-training quantization (PTQ) compression on agentic benchmarks, ensuring high quality while reducing memory usage. Read it here:

2026.08.27 20:45

Use PyTorch-native libraries within the NVIDIA NeMo Framework to customize models to hit your exacting requirements for latency, speed, memory, and compute. @NVIDIA's blog demonstrates how quantization-aware distillation (QAD) improves the Nemotron 3.5 Lightning model using NVIDIA Model Optimizer. We walk through the entire training pipeline, and show how QAD consistently outperforms post-training quantization (PTQ) compression on agentic benchmarks, ensuring high quality while reducing memory usage. Read it here: