ReCUBE Benchmark Reveals GPT-5 Scores Only 37.6% on Repository-Level Code Generation

Researchers introduce ReCUBE, a benchmark isolating LLMs' ability to use repository-wide context for code generation. GPT-5 achieves just a 37.57% strict pass rate, showing the task remains highly challenging. ReCUBE Benchmark Reveals GPT-5 Scores Only 37.6% on Repository-Level Code Generation A new benchmark called ReCUBE, introduced in a March 2026 arXiv paper, isolates and measures a critical weakness in today's large language models (LLMs) for code: their ability to leverage repository-level context. The results are sobering. Even the most advanced models, including GPT-5, struggle significantly, achieving a strict pass rate of just 37.57% in the most direct test. The work also proposes a toolkit, Caller-Centric Exploration (CCE), which boosts agent performance by up to 7.56%, pointing toward a more structured approach to navigating complex codebases. This research arrives amid a surge of activity on arXiv related to LLMs and Retrieval-Augmented Generation (RAG), with over 50 artic