75% faster. 61% cheaper. What Swimm does for Claude Code.

SwimmBench, an internal benchmarking tool developed by Swimm, evaluates the performance of AI coding assistants by comparing pre-indexed comprehensive code understanding with native codebase exploration capabilities. The tool was tested on a nearly 5 million line codebase of ScummVM, a complex open-source project, to assess the cost, speed, and quality of AI responses to architectural and explanation tasks. The results demonstrated significant cost savings and faster response times with the Swimm Deep Index approach, which provides AI with immediate relevant context, reducing exploration overhead and improving cache utilization. This approach also consistently improved quality metrics, highlighting the importance of context quality in AI-assisted coding tasks. The findings suggest that integrating a comprehensive understanding layer can enhance the efficiency and effectiveness of AI coding assistants, offering potential infrastructure savings and productivity improvements for enterprise-level deployments.