Three coding tools already blend local and cloud AI models — but smart routing remains unsolved

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A question on r/LocalLLaMA about running local and cloud models together in a single coding workflow prompted a detailed investigation into what tools actually support this. Three open-source coding agents — Cline, Aider, and Continue — already enable hybrid model use by assigning different models to distinct roles such as planning, editing, autocomplete, and commit messages. Unlike proxy solutions such as LiteLLM, these tools allow a local model and a cloud model to divide labour within the same task session. However, none of these harnesses dynamically select a model based on the specific requirements of a subtask at runtime — that capability does not yet exist in any shipping tool. The gap persists because the context needed to make such decisions is generated during planning but is never passed down to the model-selection layer.

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