Increasing Inference Effort
An inference strategy that, without switching models, trades more reasoning steps, sampling runs, chain-of-thought length, or voting aggregation for higher accuracy. Cost growth is typically linear or estimable and does not introduce additional model-call chains.
Timeline (last 90 days)
If the goal is merely to make the model a bit smarter, directly increasing inference effort is usually a more direct means than introducing advisor pairing, because it does not require adding an extra model invocation chain and its cost curve is more predictable.
When purely pursuing accuracy improvements, increasing inference effort is generally the default option with more predictable cost and lower engineering risk; advisor pairing is better suited to scenarios where inference effort is already saturated, or where another perspective rather than more compute is needed.
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If the goal is merely to make the model a bit smarter, directly increasing inference effort is usually a more direct means than introducing advisor pairing, because it does not require adding an extra model invocation chain and its cost curve is more predictable.
50%UnverifiedWhen purely pursuing accuracy improvements, increasing inference effort is generally the default option with more predictable cost and lower engineering risk; advisor pairing is better suited to scenarios where inference effort is already saturated, or where another perspective rather than more compute is needed.
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