In the news
Developing Nemotron 3.5 Lightning NVFP4 with QAD Using NVIDIA Model Optimizer
NVIDIA Developer · Published · 3 min read
In 30 seconds
- What happened
- NVIDIA released Nemotron 3.5 Lightning NVFP4, a quantized model achieving 4x throughput and 22GB size using quantization-aware distillation with Model Optimizer.
- Why it matters
- Engineers deploying large language models who need to balance memory constraints with inference speed and accuracy on production systems.
- Watch out
- QAD requires careful PTQ recipe selection and extended training with long sequences; results depend heavily on calibration data and distillation dataset quality.
Listen to this summary
- throughput
- latency
- nemotron
Who else ran this
- Announcing Day-0 Support for NVIDIA Nemotron 3.5 Lightning on vLLMvLLM
- NVIDIA Nemotron 3.5 LightningOllama
- Small Model, Big Leverage: What We Learned Fine-Tuning NVIDIA Nemotron 3.5 Lightning with an Autonomous AgentFastino
- Introducing NVIDIA Nemotron 3.5 LightningBaseten
- NVIDIA Nemotron 3.5 Lightning Delivers Fast, Accurate Specialized Task Execution for Long-Running AgentsNVIDIA Developer
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