Gemini 3 Pro vs. GPT-5.1 Codex-Max vs. Claude Opus 4.5: AI Coding Benchmark (www.hansreinl.de)

A recent benchmarking test evaluated three AI coding models—Gemini 3 Pro, GPT-5.1 Codex-Max, and Claude Opus 4.5—against the challenge of developing a Minimum Viable Product (MVP) for an application called Speakit. The models were assessed on aspects such as performance speed, code quality, and feature completeness, revealing significant disparities in their capabilities. Gemini 3 Pro emerged as the top performer, delivering a solid balance of speed and clean code structure but struggled with certain functionalities like authentication. In contrast, GPT-5.1 Codex Max introduced a unique tech stack and successfully implemented PDF text extraction, though it suffered from accessibility issues and a fragile build process. Claude Opus 4.5 presented impressive UI designs but fell short in critical functionalities, generating excessive lines of code with limited feature success. This benchmarking is significant as it illustrates the current state of AI in software development, revealing that high benchmark scores do not necessarily result in production-ready applications. It underscores the necessity for human oversight, with each AI model showcasing strengths and weaknesses that require careful management. Consequently, developers must recognize the unique traits of each AI assistant: Gemini for efficient engineering, Claude for design-heavy projects, and GPT-5.1 for flexibility, while retaining their role as senior engineers to ensure high-quality software is ultimately produced.