What can you actually do with a small language model? Three real use cases
CurieuxExplorer · x · 2026-09-08
A KDnuggets article argues that "small models don't know enough" is a poorly calibrated objection: no model is a dependable store of facts, and benchmark scores don't predict knowledge reliability. The real reasons to run an SLM (≤8B params) locally are data that can't leave the building, compute you've already paid for, and latency as the product. SLMs remain clearly weak at extended reasoning, especially hard math and complex code generation, but handle the three scenarios well without fine-tuning.
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