How to make a fast dynamic language interpreter
zef-lang.dev
April 21, 2026
30 min read
🔥🔥🔥🔥🔥
59/100
Summary
Zef is a dynamic language with an extremely simple AST-walking interpreter that has been optimized for speed. The optimizations aim to make Zef competitive with established interpreters like Lua, QuickJS, and CPython.
Key Takeaways
- The Zef interpreter achieved a speed-up of 16.6 times through various optimizations, making it competitive with established interpreters like Lua, QuickJS, and CPython.
- Key optimization techniques included value representation, inline caching, and improvements to the object model.
- A benchmark suite called ScriptBench1 was created to evaluate the performance of the Zef interpreter against classic language benchmarks.
- The Zef interpreter's performance was compared to other interpreters, showing significant improvements in speed with each optimization applied.
Community Sentiment
Positives
- Wren's design choices, such as giving up dynamic object shapes, significantly enhance performance by simplifying method lookup, which is a crucial factor for dynamic language interpreters.
- The detailed breakdown of performance improvements in the article allows for a clearer understanding of how specific changes contribute to interpreter speed, which is often overlooked in other performance analyses.
- LuaJIT is recognized as a leading optimized VM for dynamic languages, demonstrating that a small and suitable language can achieve remarkable speed, highlighting the importance of language design in performance.
- The comparison of interpreter sizes reveals that Zef is impressively compact, suggesting that efficient design can lead to significant reductions in resource usage.
Concerns
- The performance improvements discussed may not reflect real-world scenarios, as indicated by concerns over the specific benchmark used, which could misrepresent typical code performance.
- There is skepticism about the effectiveness of certain optimizations, particularly regarding dynamic dispatch, which can be a major bottleneck for naive interpreters, raising questions about their applicability.