GPT-5.6 Luna
GPT-5.6 model optimized for cost-sensitive workloads
GPT-5.6 Luna is OpenAI's fastest and most cost-efficient GPT-5.6 model release, intended for cost-sensitive, high-volume workloads. The API docs list text input/output, image input, reasoning token support, and a 1,050,000-token context window.
Pricing
Model Intelligence
Recent stories
Practitioners reported better Codex multi-agent runs by raising concurrency and splitting work across Sol, Terra, and Luna. One workflow sends deploy tasks to Luna Max to preserve Sol tokens.
New tests showed DeepSeek V4 Flash as cheaper per token and faster on some serving paths. Ramp said it cost 3x more than GPT-5.6 Luna per SWE-Bench task because it used more turns.
Sol-advisor routes Codex tasks through GPT-5.6 Sol, Luna, and Terra, while users compare Luna Max as a lower-cost reasoning setting. Early reports say small routing tests need larger benchmarks.
OpenAI said GPT-5.6 Luna pricing fell 80%, while Terra fell 20%. Codex users recommended max reasoning for linting, tests, and dependency work, but cautioned against forcing Luna into subagent roles.
OpenAI said GPT-5.6 Luna is 80% cheaper and Terra is 20% cheaper, with lower usage burn in Codex and ChatGPT Work. Sol Fast adds up to 2.5x speed at 2x price, and gateways reflected the new pricing.
OpenAI posts said GPT-5.6 Sol helped post-train GPT-5.6 Luna, framing Sol as a research agent rather than just a coding model. Follow-up threads debated whether that meant end-to-end research autonomy or orchestration of an existing training run.