local-ai-inference

Running models on your own hardware instead of renting frontier compute by the token. This area covers the shift toward small specialized models, on-device and on-premise deployment, and routing architectures that send each task to the cheapest capable model. Expect practical guidance on hardware requirements, quantization, latency and cost tradeoffs, and the privacy and control benefits of keeping inference in-house rather than calling external APIs.

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