Codex GPT-5.6-sol Performance Tracker (marginlab.ai)

A new performance tracker for the Codex gpt-5.6-sol AI model has been launched to monitor and analyze its effectiveness on software engineering (SWE) tasks. This tracker updates daily and employs statistical testing to identify significant regressions in Codex's performance, making it a vital tool for detecting declines in capabilities that could impact developer productivity. By benchmarking directly within the Codex CLI—without using a custom agent—this initiative offers an accurate reflection of real-world usage, thereby enhancing its relevance for the AI/ML community. The tracker evaluates the model against a carefully curated subset of SWE-Bench-Pro and records various performance metrics, including pass rates, input/output token usage, and execution times. With a baseline pass rate of 83.40% derived from extensive trials, significant degradations are flagged when observed pass rates fall below this threshold with a strong statistical confidence. By providing insights into both daily variability and longer-term performance trends, the tracker serves as an essential resource for developers and researchers aiming to better understand and improve AI coding assistants.