Introducing GPT-6 Sol and Luna

OpenAI has announced the expansion of its GPT-6 model lineup with the introduction of GPT-6 Sol and Luna, designed to bring frontier intelligence to everyday work while balancing capability and cost. Trained using methods similar to the flagship GPT-6 Astra model, Sol and Luna deliver state-of-the-art performance in professional tasks, factuality, coding, and computer use at higher speed and lower cost. According to OpenAI, API prices for Sol and Luna are reduced by 50% compared to their GPT-5.6 promotional pricing. On industry benchmarks such as AutomationBench, FrontierCode, and DeepSWE v1.1, GPT-6 Sol and Luna compete closely with or outperform major competitor models while operating at substantially lower costs per task. In addition to lower token prices, OpenAI has updated its prompt caching infrastructure to deliver higher cache hit rates by default, providing discounts of 90% on cached input-token reads. Developers can now use a Prompt Caching Dashboard, diagnostics tools, explicit breakpoints, and flexible reasoning effort controls to optimize cache reuse without breaking context. GitHub reported that these enhancements reduced the share of prompt tokens requiring fresh processing by over 50% across billions of requests. Furthermore, Sol and Luna inherit the improved communication style and alignment work introduced with GPT-6 Astra, resulting in clearer technical and coding interactions.