https://lesitedefrancois.be/en/tags/microservices/Recent content in Microservices on Le Site de FrançoisHugo -- gohugo.ioen© 2026 Françoishttps://lesitedefrancois.be/en/ai/nim/Mon, 01 Jan 0001 00:00:00 +0000https://lesitedefrancois.be/en/ai/nim/<p><strong>NIM (NVIDIA Inference Microservices)</strong> are <strong>container images</strong> and Helm charts that deliver ready-to-run <strong>inference endpoints</strong> for specific models (LLMs, vision, embedding, reranking, and more). The objective is to shrink time-to-production: instead of assembling CUDA drivers, frameworks, model weights, and an OpenAI-compatible server yourself, operators pull a NIM that bundles a performance-tuned engine (often <strong>TensorRT-LLM</strong> or Triton-backed paths), default model artifacts or download hooks, health checks, and a stable HTTP/gRPC API. NIMs are sized for <strong>GPU</strong> deployment and target enterprise MLOps teams that want versioned, scannable containers with predictable resource requests rather than bespoke notebooks turned into scripts.</p>