GPT-5.6 Luna vs. GPT‑5.6‑Cyber

GPT-5.6 Luna is the lowest-cost model in OpenAI’s GPT-5.6 family, built for fast and affordable AI assistance across everyday and technical workflows. The GPT-5.6 lineup includes Sol as the flagship model, Terra as the balanced model for everyday work, and Luna as the efficient model for users who need strong capability at lower cost. Luna is intended for developers, businesses, and teams that need scalable AI for coding help, workflow automation, research support, analysis, customer-facing applications, and high-volume API usage. In the pasted preview text, Luna is presented as part of the same GPT-5.6 release process and benchmark set as Sol and Terra. It appears in evaluations for command-line coding workflows, long-horizon biology tasks, ExploitBench, and ExploitGym, indicating that it is designed to handle more than simple chat use cases. The model is priced at a lower per-token rate than Sol and Terra, making it more suitable for applications where cost efficiency is a major priority. GPT-5.6 Luna also supports the new GPT-5.6 prompt caching approach, including explicit cache breakpoints, a 30-minute minimum cache life, cache writes billed above the uncached input rate, and discounted cached-input reads. Like the rest of the GPT-5.6 family, Luna is developed with layered safeguards matched to model capability. These safeguards include trained refusals for prohibited cyber assistance, real-time misuse classifiers, paused generation for higher-risk cases, account-level review, monitoring, enforcement, automated red-teaming, and third-party human expert red-teaming. Luna is expected to support legitimate defensive and technical workflows such as code review, debugging, patch development, security education, and defensive testing while making prohibited misuse more difficult and detectable. GPT-5.6 Luna helps organizations deploy GPT-5.6-class AI where speed, affordability, scalability, and safe production use are the most important requirements.

GPT-5.6-Cyber is OpenAI’s cybersecurity-specific model for approved defenders who need advanced capabilities for authorized security research and defensive operations. The model is available through Daybreak Red and is built on GPT-5.6 Sol with additional training for specialized cybersecurity tasks. It is designed to improve support for vulnerability discovery, exploit validation, security testing, exploit-chain reasoning, malware analysis, incident response, secure code review, patch validation, and vulnerability report writing. OpenAI introduced GPT-5.6-Cyber as part of an expanded Daybreak program that gives trusted defenders access to advanced AI capabilities before offensive AI is widely deployed by attackers. Daybreak Blue gives approved users access to frontier general-purpose models with defensive-security safeguards, while Daybreak Red provides access to purpose-trained cybersecurity models for more advanced authorized work. GPT-5.6-Cyber is intended to reduce unnecessary refusals in legitimate research scenarios that still require careful oversight because of their dual-use nature. OpenAI reports that the model performs strongly on internal cybersecurity completion evaluations and improves on certain benchmark tasks related to exploit development and vulnerability research. The model has also been used by OpenAI researchers to study real-world software, identify vulnerabilities, and support coordinated vulnerability disclosure. Access to Daybreak is controlled through identity verification, account security, monitoring, legal attestations, approved-use restrictions, and additional protective measures. OpenAI recommends sandboxing and isolating security workflows, monitoring agent actions, using auto-review mode, defining scope clearly, and enforcing permissions for higher-risk work.