Inside Zig's Incremental Compilation: Rebuilds in Milliseconds, Not Seconds

A member of Zig’s core team walks through how the language’s incremental compilation now works well enough for daily production use. The system detects which individual functions and declarations changed since the last build, recompiles only those, and patches the resulting bytes directly into the output binary. In a demo on a real pixel-editor app, an initial 5-second build drops to 50–70ms rebuilds after each edit. The feature ships in 0.16.0 but depends on linker work that only lands fully in the 0.17.0 release, so users on tagged versions must wait or switch to master.

The compiler pipeline splits into stages that each lend themselves to caching. Source files are parsed and lowered into an untyped SSA form called ZIR, a step that is a pure function of file contents with no shared state — making it embarrassingly parallel and trivial to cache on disk, since Zig’s data-oriented layout lets ZIR be read and written with a single system call rather than a serialization pass. This part has been fast and battle-tested for years. The hard problem is semantic analysis: type checking and comptime evaluation.

To make that stage incremental, Zig models compilation as discrete “analysis units” — a type’s layout, a declaration’s type, a const’s value, or a runtime function body — connected by a dependency graph built as each unit is analyzed. When a function reads globals, the compiler records exactly what it depends on (a variable’s type, a constant’s comptime value), so a change only forces re-analysis of the units that actually touch it. The author notes this is where language design matters most: Zig has been deliberately, sometimes controversially, reshaped over the years to keep this dependency tracking tractable, which is what separates its approach from compilers that can only cache the easy front-end stages.