As the author of Tera mentioned in the article, I am curious how it can get 2x faster. Was the benchmark using tera v2 with the `fast` feature enabled?
They were with tera 2.1.0, however using the default settings and not enabling the `fast` feature (which I did not know about, TIL).
The comparison benchmark results in the post were older and prior to further passes. After updating to tera 2.4.0 and enabling the `fast` feature set, I reran the benchmarks against the current codebase and the difference between my Rust crate and Tera is now about ~1.5x.
Some of the technical differences are (which in disclosure were surfaced by GPT 5.6 Sol): context and loop values are borrowed while Tera clones, cached static positions/lookups, less per-render heap setup, escaping chunks directly into the final String instead of bytes, and more granular bytecode functions which avoid stacks.
They were with tera 2.1.0, however using the default settings and not enabling the `fast` feature (which I did not know about, TIL).
The comparison benchmark results in the post were older and prior to further passes. After updating to tera 2.4.0 and enabling the `fast` feature set, I reran the benchmarks against the current codebase and the difference between my Rust crate and Tera is now about ~1.5x.
Some of the technical differences are (which in disclosure were surfaced by GPT 5.6 Sol): context and loop values are borrowed while Tera clones, cached static positions/lookups, less per-render heap setup, escaping chunks directly into the final String instead of bytes, and more granular bytecode functions which avoid stacks.