Most validation libraries like Zod create deep clones of your data during validation, which can impact performance in high-throughput applications. I built decode-kit to take a different approach: assertion-based validation that validates and narrows TypeScript types in-place, without any copying or transformation. Here's what the API looks like in practice:
import { object, string, number, validate } from "decode-kit";
// Example of untrusted data (e.g., from an API)
const input: unknown = { id: 123, name: "Alice" };
// Validate the data (throws if validation fails)
validate(input, object({ id: number(), name: string() }));
// `input` is now typed as { id: number; name: string }
console.log(input.id, input.name);
When validation fails, decode-kit takes an equally thoughtful approach. Rather than being prescriptive about error formatting, it exposes a structured error system with an AST-like path that precisely indicates where validation failed. It does include a sensible default error message for debugging, but you can also traverse the error path to build whatever error handling approach fits your application - from simple logging to sophisticated user-facing messages.
The library also follows a fail-fast approach, immediately throwing when validation fails, which provides both better performance and clearer error messages by focusing on the first issue encountered.
I'd love to hear your thoughts and feedback on this approach.
Hey, I did some benchmarks if you're interested - benchmarks results are in the README.md.
https://github.com/nimeshnayaju/zod (Fork of Zod's repo which already included benchmarks comparing Zod 4 against Zod 3, so I simply integrated my validation library)
I was surprised by the source including a bunch of try/catch, which results in deopts for that code path as far as I understand, given that the stated benefit over Zod and other validators was that this should be run in performance critical code. I’d be curious to see benchmarks that show whether this is faster than zod, valibot, and zod4 mini in hot code paths.
It would be nice to provide some benchmarks comparing it to Zod, arktype, etc.
Comparing it across different runtimes (Node.js, Bun, web browsers, etc.) would be great, too.
Hey, I did some benchmarks if you're interested - benchmarks results are in the README.md.
https://github.com/nimeshnayaju/zod (Fork of Zod's repo which already included benchmarks comparing Zod 4 against Zod 3, so I simply integrated my validation library)
14 comments
[ 3.0 ms ] story [ 31.7 ms ] threadimport { object, string, number, validate } from "decode-kit";
// Example of untrusted data (e.g., from an API) const input: unknown = { id: 123, name: "Alice" };
// Validate the data (throws if validation fails) validate(input, object({ id: number(), name: string() }));
// `input` is now typed as { id: number; name: string } console.log(input.id, input.name);
When validation fails, decode-kit takes an equally thoughtful approach. Rather than being prescriptive about error formatting, it exposes a structured error system with an AST-like path that precisely indicates where validation failed. It does include a sensible default error message for debugging, but you can also traverse the error path to build whatever error handling approach fits your application - from simple logging to sophisticated user-facing messages.
The library also follows a fail-fast approach, immediately throwing when validation fails, which provides both better performance and clearer error messages by focusing on the first issue encountered.
I'd love to hear your thoughts and feedback on this approach.
would this mask any errors that would occur later in the validation?
https://github.com/nimeshnayaju/zod (Fork of Zod's repo which already included benchmarks comparing Zod 4 against Zod 3, so I simply integrated my validation library)
https://github.com/nimeshnayaju/valibot-benchmarks (An unofficial benchmark suggested in another comment comparing Valibot against Zod)
https://github.com/nimeshnayaju/zod (Fork of Zod's repo which already included benchmarks comparing Zod 4 against Zod 3, so I simply integrated my validation library)
https://github.com/nimeshnayaju/valibot-benchmarks (An unofficial benchmark from another user comparing Valibot against Zod)
They show a lot of potential and promising results. Any guess why Valley is slower for parsing objects with primitive values?