How Reasoning Effort Settings Are Built Into LLMs Through Training

The article explains how reasoning models can offer multiple effort modes, separating training-time methods from inference-time controls such as system prompts and chat templates.

It compares six open-weight models, including DeepSeek V4, Nemotron 3 Ultra, Kimi K2.5, GLM-5, Qwen3, and Inkling, noting that their reports disclose different levels of detail.

It also shows how GPT-5.6's model selection and effort settings act as two separate scaling axes.