75% faster. 61% cheaper. What Swimm does for Claude Code.
This title could be clearer and more informative.Try out Clickbait Shieldfor free (5 uses left this month).
Swimm published benchmark results from SwimmBench, an internal tool measuring how pre-indexed code context affects Claude Code performance on a ~5M line C++ codebase (ScummVM). Testing compared Swimm's Deep Index (pre-computed code understanding) against Claude Code's native exploration. Results show 75% faster response times and 61% lower token costs when using indexed context, primarily because the AI skips file traversal and grep operations. The benchmark measures cost, latency, quality, and tool usage across architectural questions and explanation tasks. Swimm acknowledges limitations: internal testing with inherent bias, single codebase, and no external validation. The post targets engineering leaders evaluating AI tooling ROI at scale.
Table of contents
The problem: AI coding assistants are expensive and slow on large codebasesWhat we built: SwimmBench – a benchmarking tool for AI code tasksThe test: ScummVM – 4.87 million lines of production C++Results: What we foundMethodology notes and limitationsWhy this matters for development leadersHow Swimm fits inSort: