Serve LLMs with SGLang on DGX Station (Qwen3-8B default; Qwen3.6 MoE optional)—prefix-cached multi-turn, structured output, benchmarks, and inference-server guidance
Extract false-positive and false-negative gaps from VLM binary-classification-question (BCQ, yes/no) predictions. Use when the user asks to "analyze VLM BCQ gaps", "extract VLM false positives and false negatives", or identify failure cases from a predict
Practical guidance for training MoE VLMs in Megatron Bridge. Compares FSDP and 3D-parallel approaches, using rounded lessons from Qwen3-VL, Qwen3-Next, and other multimodal experiments.
Fine-tune popular AI models faster in Unsloth with NVIDIA RTX AI PCs, RTX PRO workstations, and DGX Spark—plus explore the new Nemotron Nano 3 family of open models.
Build advanced AI agents for providers and patients using this developer example powered by NeMo Microservices, NVIDIA Nemotron, Riva ASR and TTS, and NVIDIA LLM NIM
