Can I realistically get close to Claude/Codex capabilities locally?

The article discusses the challenges of running large language models (LLMs) like Claude and Codex locally on a modest hardware setup, specifically a 32GB rig with Nvidia GPUs. The user is seeking open weight models that can match the context and coding capabilities of Opus, particularly with a focus on models like GLM 5.2, Qwen 3.7, and Kimi K 2.7, while expressing concerns over privacy and token independence. The discussion highlights the need for efficient model architectures and hardware upgrades to handle larger context windows and improve performance for software engineering tasks.