OPEN LINK ↗
// 1h agoPRODUCT UPDATE
OpenAI clarifies GPT-5.6 reasoning effort levels
In response to developer questions about token consumption and model performance, OpenAI's Nik Pash clarified that reasoning effort levels (like "xhigh") are rough product labels rather than fixed, apples-to-apples token budgets across model versions. Because GPT-5.6 spans a wider capability range than GPT-5.5, the "xhigh" setting on GPT-5.6 is not equivalent to the same setting on GPT-5.5 and can consume significantly more tokens to execute deeper reasoning.
// ANALYSIS
Defining reasoning effort by abstract labels rather than explicit token limits makes cost prediction a nightmare for builders, but it is the only way providers can scale model intelligence dynamically.
- –Comparing effort settings (like xhigh) across different model versions is a false equivalence because newer architectures allocate reasoning resources differently.
- –The expanded range of GPT-5.6 indicates it can scale reasoning tasks much deeper, leading to higher token consumption but potentially much better outcomes on complex tasks.
- –Developers must transition from static token-based routing to dynamic outcome-based evaluation to keep costs manageable as reasoning effort levels evolve.
// TAGS
gpt-5.6openaireasoning-efforttoken-efficiencyartificial-intelligencellms
DISCOVERED
1h ago
2026-07-10
PUBLISHED
1h ago
2026-07-10
RELEVANCE
8/ 10
AUTHOR
pashmerepat