GPT-5.6 Sol's 5 reasoning levels mapped — which task fits where
openai's vaibhav srivastav revealed which of gpt-5.6 sol's five reasoning levels—ranging from 'light' to 'ultra'—fit specific task complexities. this guidance helps users balance accuracy against token costs.
openai's vaibhav srivastav released a guide for the new gpt-5.6 sol model, explaining that its 'light' and 'low' levels suit quick tasks, while 'medium', 'high', and 'xhigh' are designed for increasing complexity and verification needs. the 'max' setting extends compute time for single problems, whereas 'ultra' deploys multiple sub-agents in parallel to tackle different parts of a task simultaneously. higher levels significantly increase token usage, leading srivastav to recommend starting at lower settings and scaling up only when necessary. this system introduces complexity contrary to openai's goal of a 'no interface' experience, requiring users to carefully benchmark to find the optimal cost-to-quality ratio.