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Choosing GPT-5.6 Sol, Terra, or Luna in Codex
GPT-5.6 splits its operational workload across Sol, Terra, and Luna models to match agent capabilities to the complexity of the coding task.
What: OpenAI's GPT-5.6 categorizes tasks into three buckets: Sol for high-value/ambiguous problems, Terra for routine implementation, and Luna for fast, bounded tasks. 'Sol Ultra' is specifically reserved for multi-agent coordination and deep reasoning.
Why it matters: This tiered model deployment strategy reflects a move away from 'one-size-fits-all' LLMs toward specialized model routing based on cost and reasoning complexity.
Takeaway: When using GPT-5.6 for coding, explicitly define your task's goals, boundaries, and expected completion checks in the prompt to help the agent route the request correctly.
Original article
Choosing GPT-5.6 Sol, Terra, or Luna in Codex
Codex for moonshots and everything in between Some missions demand deep planning and coordination. Others are a straight shot. The same is true of the work you hand to Codex, which is why GPT-5.6...
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