Why I Switched from Node.js to Bun for AI Backends (Benchmarks Inside)

#bunjs #node #javascript #ai

I run AI agents that make hundreds of API calls per minute. Node.js was the bottleneck. Then I tried Bun.

The Numbers

Metric	Node.js 22	Bun 1.3	Difference
Startup	200ms	12ms	16x faster
HTTP requests/sec	45,000	110,000	2.4x faster
SQLite reads	0.8ms	0.4ms	2x faster
Memory (idle)	45MB	22MB	2x less
npm install	12s	2s	6x faster

Why It Matters for AI

AI backends have a unique workload:

High HTTP throughput — proxying LLM API calls
SQLite for state — conversation history, CRM data
Fast startup — serverless/edge deployments
Low memory — running on constrained devices (Raspberry Pi)

Bun wins on all 4.

My Stack

import { Hono } from "hono";
import { Database } from "bun:sqlite";

const app = new Hono();
const db = new Database("app.db");

// SQLite with WAL mode — 0.4ms reads
db.exec("PRAGMA journal_mode=WAL");
db.exec("PRAGMA cache_size=64000");

app.post("/chat", async (c) => {
  const { message } = await c.req.json();
  // Call Claude API
  const response = await fetch("https://api.anthropic.com/v1/messages", {
    method: "POST",
    headers: { "x-api-key": process.env.ANTHROPIC_API_KEY },
    body: JSON.stringify({ model: "claude-sonnet-4-20250514", messages: [{ role: "user", content: message }] })
  });
  return c.json(await response.json());
});

export default { port: 3000, fetch: app.fetch };

That's a complete AI backend in 15 lines.

The Gotchas

Not all npm packages work — native addons may need recompilation
Debugging — Node.js debugger is more mature
Production stability — Bun is stable but Node has 15 years of battle-testing

For AI backends specifically? Bun is the clear winner.