GPT-5.6 Luna enters the lineup as the budget-oriented member of the GPT-5.6 trio introduced alongside the flagship Sol and the balanced Terra, sitting at the entry point of the family rather than competing on raw frontier intelligence. It is aimed squarely at bulk, predictable workflows such as classification pipelines and structured data extraction, where token cost and throughput matter more than the deepest reasoning ceiling. The deliberate positioning gives teams a low-friction option for routing routine traffic, freeing the more expensive tiers for harder problems.

On the technical side, Luna ships with a 1.05-million-token context window and supports reasoning, vision, tool calling, and web search, making it flexible enough for long-document and multimodal pipelines despite its efficiency focus. The headline shift is the steep price drop applied across the tier, which markedly improved its cost-per-token position and made it viable for very large batch processing. Combined with support for structured output and standard tool integrations, it is a practical fit for production agents, document triage, and other high-volume assistants where stability and price matter more than frontier benchmarks.