Why Most SLM Deployments Fail Before They Start

Seventy-eight percent of enterprises are running an AI pilot. Only 14% have scaled one to production. The reason is rarely the model. It is a selection process that treats a leaderboard score as a deployment decision.

This white paper lays out the variables that actually determine whether a small language model performs on your hardware, including quantization recipe, execution mode, KV cache budget, and concurrency behavior under real workload conditions. It also walks through the production-grade selection process that surfaces them, before a single fine-tuning run starts.

Download the paper to see the data behind partial quantization, throughput sweeps on constrained GPUs, and the questions to ask before choosing a model.