Scaling AI Inference with Nutanix Enterprise AI: Sharding, Instances, KV Cache and Agent Gateway

General

When discussing AI inference infrastructure, the word “scaling” can mean several very different things. We might need more GPUs because a model is too large for a single GPU, more copies of a model because concurrency is increasing, or better routing between those copies because repeated context is consuming unnecessary compute. Eventually, we may also […]

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LLMs vs SLMs: Why Smaller Models Could Power the Future of Agentic AI

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InfrastructureTechnology

The AI landscape has been dominated by Large Language Models (LLMs)—massive neural networks trained on trillions of tokens, spanning hundreds of billions of parameters. These models, such as GPT-4 or Claude, have shown remarkable general-purpose intelligence, but they come with steep costs: enormous compute requirements, GPU dependency, and operational overheads that make them inaccessible for […]

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