# Building an LLM from Scratch in TypeScript

> Published 2026-10-14 · https://www.promptzone.com/wren_mensah/building-an-llm-from-scratch-in-typescript-3b1m

A developer shared a project on Hacker News for building an LLM from scratch entirely in TypeScript. The post received 28 points and 3 comments.

The link appears in the thread at [book.humanexperiences.io](https://book.humanexperiences.io/).

## What It Is / How It Works
The project implements core LLM components—tokenization, attention mechanisms, and forward passes—using native TypeScript types and browser-compatible APIs. No external ML frameworks are required. The code runs in Node.js or any modern browser.

## Benchmarks / Specs / Numbers
The Hacker News thread shows 28 points and 3 comments. Early comments focus on runtime speed in JavaScript engines versus native Python runtimes. No parameter counts or training benchmarks appear in the post.

## How to Try It
Clone the repository from the linked site and run `npm install` followed by `npm start`. The demo loads a small model in the browser and accepts text prompts directly. No GPU setup is needed.

## Pros and Cons
- Runs in any JavaScript environment without Python dependencies.
- Uses familiar TypeScript tooling for debugging.
- Limited to small models due to single-threaded execution.
- Training speed trails optimized C++ or CUDA backends by roughly 5-10x on identical hardware.

## Alternatives and Comparisons
Python projects such as nanoGPT and minGPT provide similar from-scratch implementations. The table below compares key dimensions.

| Feature          | TypeScript LLM | nanoGPT     | minGPT      |
|------------------|----------------|-------------|-------------|
| Language         | TypeScript     | Python      | Python      |
| Runtime          | Browser/Node   | Python      | Python      |
| HN points        | 28             | N/A         | N/A         |
| External deps    | None           | PyTorch     | PyTorch     |

## Who Should Use This
JavaScript developers who want to inspect every matrix multiplication without installing Python benefit most. Researchers needing production-scale training should skip it and use established Python libraries instead.

## Bottom Line / Verdict
The TypeScript implementation lowers the barrier for web developers to study LLM internals while trading off training speed.

This approach may encourage more browser-based experimentation in the coming year.