The Open Evaluation Standard: Benchmarking NVIDIA Nemotron 3 Nano with NeMo Evaluator

Accelerating Transformers Fine-Tuning with NVIDIA NeMo AutoModel

Welcome the NVIDIA Llama Nemotron Nano VLM to Hugging Face Hub

Measuring Open-Source Llama Nemotron Models on DeepResearch Bench

Introducing NVIDIA Nemotron 3 Nano Omni: Long-Context Multimodal Intelligence for Documents, Audio and Video Agents

TokenPowerSandbox: Evidence-Gated CPU-First Screening for Energy-Aware LLM Serving

TokenPowerSandbox is an evidence‑gated workflow that uses a CPU‑resident projector, brief GPU probes, full‑workload verification, and tamper‑evident provenance to predict energy usage of large language model serving. In experiments on an NVIDIA H100 80GB running Qwen2.5‑7B‑Instruct with vLLM, the method achieved energy MAPE of 6.23% and 7.35% on blind holdout and no‑refit confirmations, with high Spearman rank correlations. A predeclared TTFT gate demonstrated that energy accuracy alone cannot guarantee latency, as it passed at concurrency four but abstained below that level.

Mistral AI partners with NVIDIA to accelerate open frontier models