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tech 31 July 2026

Speeding Up the Rust Compiler in July 2026: Strategies and Improvements

Explore how recent improvements have reduced Rust's compilation time by 5.59% with key optimizations in rustdoc and Clippy.

Article inspired by the original source
How to speed up the Rust compiler in July 2026 ↗ nnethercote.github.io

Introduction

In July 2026, the Rust community continues to demonstrate its commitment to efficiency and performance. Since December 2025, the Rust compiler has seen a significant wall-time reduction of 5.59%, underscoring the ongoing efforts to optimize this crucial tool for developers. In this article, we'll delve into the details of these improvements, particularly through rustdoc and Clippy.

Rustdoc: Significant Improvements

The team behind Rustdoc has achieved remarkable progress with an average wall-time reduction of 37.92%. These improvements mainly stem from pull requests #159623, #159721, #159779, and #159854 by Noah Lev, who reduced the workload required when processing impls. A peculiar bug was the catalyst for these changes, demonstrating how unexpected issues can lead to innovative solutions.

The Impact of PGO

Additionally, the integration of rustdoc benchmarks into the PGO training set, thanks to Jakub Beránek (#159091), added a further 2.85% reduction in wall-time. PGO optimization is known to be complex to set up but can dramatically transform performance, as evidenced by these results.

Clippy: A Performance Boost

Clippy, the well-known linting tool, has also benefited from major performance enhancements. PRs #17124 and #17132 by xmakro eliminated unnecessary calls, significantly reducing processing time. By combining passes to avoid empty check_foo method calls, xmakro effectively optimized the process.

Conclusion

These improvements highlight the importance of continuous optimization in software development. With a 5.59% reduction in compilation time, Rust once again proves its commitment to efficiency and developer satisfaction. For decision-makers and developers, these advancements emphasize the value of investing in ongoing optimization practices.

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