# GPT 5.6 Has 72 Possible Configurations. What's A Good Default? > Source: > Published: 2026-07-09 22:33:25+00:00 # GPT 5.6 Has 72 Possible Configurations. What's A Good Default? Yes, there are probably too many options to choose from in the GPT 5.6 release. In the context of reasoning models, though, I find it interesting how these choices map onto training-time and [inference-time scaling](/glossary/#inference-time-scaling). If we loosely map the options onto the classic o1 plots, Sol, Terra, and Luna stand in for three model sizes and training budgets along the training-compute axis. The effort settings then sit on the inference-time-compute axis. The full list has three model choices and six reasoning-effort levels (Light, Medium, High, Extra High, Max, and Ultra). Once Work versus Codex and Standard versus Fast are included, the full configuration matrix becomes `Work/Codex × Sol/Terra/Luna × Light/Medium/High/Extra High/Max/Ultra × Standard/Fast` That gives us `2 × 3 × 6 × 2 = 72` possible configurations. So, what is a good default now? Luna with High effort? Sol with Light effort? Terra with Medium effort? Sure, a performance-versus-cost chart can help identify the good bang-for-the-buck combinations. For instance, Luna with Extra High effort may be better and cheaper than Sol with Medium effort. But yeah, 72 possible configurations leave us with a lot of choices 🤯. ## Read Next [Inkling: A New Open-Weight 975B MoE with a Few Surprises Short note on Thinking Machines Lab's 975B Inkling open-weight model, its benchmark profile, sparse MoE design, short convolutions, embedding RMSNorm, and](/blog/2026/inkling-architecture-benchmark-notes.html) [200,000 Subscribers Short note celebrating Ahead of AI reaching 200,000 subscribers.](/blog/2026/ahead-of-ai-reached-200000-subscribers.html) [Build a Reasoning Model From Scratch Is Out Short note announcing the release of Build a Reasoning Model From Scratch and linking the publisher and Amazon pages.](/blog/2026/build-a-reasoning-model-from-scratch-is-out.html)