Rust compiles generic code into concrete versions for the types a program uses. When substantial generic functions are instantiated for many different types, the compiler may emit more code, which can increase the final binary. It is not necessarily one complete copy per call: optimization, dead-code removal, code sharing, linking, and the target all affect what remains. The practical answer is to measure the release artifact, find what contributes to its size, and compare build or code changes against that baseline.
Why generics can increase binary size
Rust uses compile-time monomorphization: it fills in generic types and produces concrete code for the instantiations the program needs. For example, a generic function used with several distinct types can have specialized versions for those types. The compiler’s backend collects these instantiations before code generation. See the Rust Book’s explanation of generic data types and the Compiler Development Guide’s monomorphization overview.
More distinct instantiations can mean more generated code, particularly when generic function bodies are substantial. But neither the presence of generics nor the number of calls alone tells you how large the final artifact will be. Optimization and linking can remove unused code or affect how code is emitted. Treat generic instantiation as a possible cause to investigate, not proof that a binary is bloated.
First establish what is making the artifact large
- Build the configuration you intend to ship. Record the final artifact size using the same target triple, enabled features, dependency versions, and toolchain for each comparison. Development and release profiles are configured differently, so a development binary is not a reliable stand-in for the shipped release.
- Inspect sections and symbols. Determine whether the reported size comes from executable code, read-only data, debug information, or another component. Section-level inspection can distinguish a large code section from debug data that may not belong in the distributed artifact. The Embedded Rust Book’s speed-versus-size discussion demonstrates this kind of inspection.
- Change one variable at a time. Compare profile settings, source changes, and dispatch choices against the same baseline. Record artifact size along with runtime performance and compile or link time; a smaller file is not automatically a better result if it harms a requirement that matters to your project.
Compare build settings without assuming a universal winner
Cargo profiles and rustc code-generation options control different parts of the trade-off. Use the Cargo Profiles reference and rustc Codegen Options reference for the settings available to your toolchain.
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| Approach | What to compare | Trade-off to watch |
|---|---|---|
opt-level = "s" or opt-level = "z" |
Measure each level in the intended release configuration; both are optimization choices aimed at code size. | Neither guarantees the smallest output for every project or target, and optimization can affect runtime speed. |
| Link-time optimization (LTO) | Compare artifact size and runtime behavior with the LTO configuration you are considering. | LTO enables broader optimization across crates but can lengthen linking. |
codegen-units |
Compare the setting’s effect on final output and build time for your project. | Codegen units partition compilation and affect parallelism and optimization opportunities; fewer units can change optimization and build cost. |
| Debug information and stripping | Compare the distributed artifact with debug information retained versus omitted or stripped, as appropriate to your workflow. | Debug information affects artifact size and can be important for diagnosing problems. Distinguish distribution size from code-section size and keep the debugging information your development workflow needs. |
These controls interact with the target, dependencies, toolchain, and workload. Compare them individually and retain the combination that meets your size, performance, build-time, and debugging needs rather than copying a setting on the assumption that it is always smallest.
Reduce code emitted for generic instantiations
Move type-independent work out of generic functions
If a generic function contains substantial work that does not depend on its type parameter, move that work into a non-generic helper and have the generic function call it. The helper is then not specialized as part of each generic shell. This is a design technique to test, not a guaranteed size reduction: rebuild and measure the resulting artifact.
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Use fewer distinct instantiations where practical
Review where large generic functions are used with different concrete types. Reducing unnecessary type variation in those paths may reduce the number of substantial instantiations, but do not change sound API or program design merely to pursue a theoretical saving. Check the final binary to see whether the change mattered after optimization and linking.
Consider dynamic dispatch for suitable paths
A trait object can avoid specializing a path for each concrete type, but introduces runtime dispatch and affects API and design choices. It can be worth considering for cold paths or where flexibility matters more than the cost of dispatch. Compare it with the generic version under your actual workload and artifact configuration; the documentation establishes the specialization mechanism, not a benchmark result for your program.
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Interpret size examples in context
The Embedded Rust Book gives one worked embedded example in which .text changes from 9,060 bytes to 3,490 bytes and .rodata from 1,708 bytes to 1,100 bytes after the shown optimization change. Those measurements describe that example only; they are not a general Rust benchmark or a prediction of savings for desktop programs or other embedded targets.
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