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Small language models are finding a place beside larger AI systems

Not every task needs the largest available model; cost, latency, privacy and device constraints are creating room for smaller systems.

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Small language models are finding a place beside larger AI systems
Not every task needs the largest available model; cost, latency, privacy and device constraints are creating room for smaller systems.

Different tools for different jobs

Large general-purpose systems are useful when tasks are broad or ambiguous. Smaller models can be attractive when the job is narrow, repeated and sensitive to speed or cost.

Architecture becomes a product decision

Teams increasingly mix models, retrieval systems and deterministic software rather than treating one model as the entire application.

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