Abliterated model large v2: GLM 5.3 84.5% CyberGym (abliteration.ai)

Abliteration.ai has launched the abliterated-model-large-v2, a refined version of the GLM 5.3 model tailored for offensive cybersecurity applications, AI red teaming, and agent testing. This new model boasts an impressive 84.5% pass rate on the CyberGym, where it evaluated over 1,500 OSS-Fuzz bugs across 188 projects, making it a competitive option alongside other models like GPT-5.5. Additionally, it exhibits noteworthy performance on the Terminal-Bench 4.0 and ExploitGym tasks, completing 105 out of 869 tasks in a two-hour window, which highlights its capability in long-horizon coding and vulnerability exploitation. This announcement is significant for the AI/ML community as it addresses the growing need for specialized tools in cybersecurity, where traditional APIs often falter. The model utilizes FP8 hosting and allows for extensive context with 1 million tokens, all while ensuring zero data retention for user prompts and responses. Developers can seamlessly integrate this model via OpenAI-compatible endpoints, making it an accessible choice for organizations looking to enhance their cybersecurity efforts. It's a noteworthy step toward creating safer and more secure digital environments, particularly for red teamers and penetration testers.