Ivan CernjaCheapest TypeScript Backend Framework for AI Coding (2026)
Encore came in at $6.29 of token spend across three benchmark runs. NestJS came in at $12.69 for the same work with fewer passing tests.
Which TypeScript backend framework is cheapest to use with an AI coding agent like Claude Code?
When a team's day-to-day workflow involves an agent iterating on backend code, the per-iteration token cost stops being a curiosity and starts being a line item. To put numbers on the question we took Claude Code, pointed it at the same realistic backend project, and ran it on five frameworks (Encore, Express, Fastify, Hono, and NestJS) across three runs (baseline, library-augmented, and rubric-graded), tracking token spend per run. The headline finding is that across all three runs combined Encore came in cheapest at $6.29 of token spend, while NestJS came in most expensive at $12.69, which is roughly 2x for fewer passing tests on the production-readiness rubric.
Full transcripts and per-task numbers: github.com/encoredev/ai-backend-benchmark.
Total token spend across three runs
| Framework | Total token cost across all three runs |
|---|---|
| Encore | $6.29 |
| NestJS | $12.69 |
The other three frameworks (Express, Fastify, Hono) sit between those two endpoints and their full per-framework totals are in the benchmark repo alongside the raw transcripts.
Per-run highlights
Hono had the cheapest single run of the entire benchmark at $1.55 in Run 1, with Encore at $1.96 and NestJS at $2.61 (one repeat ran to $4.45) on the same run. By Run 3, when production-readiness was graded directly by the tests, Fastify hit every check at $4.60 per run, Encore hit every check at $2.58 per run, and NestJS finished at 30 of 36 checks at $5.95 per run.
Why Encore stays flat across runs
Encore's per-run cost barely moved across the three runs because the production-readiness checks the test suite added in Run 3 were already encoded in the primitives the agent had used in Run 1. The DLQ check was satisfied by a one-line retryPolicy on the existing Subscription. The structured-logging check was satisfied by switching from console.log to encore.dev/log. The versioned-migrations check was satisfied by Encore's service migrations, which the agent had already been using.
The other four frameworks all climbed across runs. In Run 2 the agent burned turns integrating pg-boss, drizzle-kit, and pino (and on some frameworks failed to land the integration at all). In Run 3 the agent iterated against the production-readiness rubric on top of the library integration work. Higher turn counts and longer transcripts compound into a higher token bill.
The cheapest run is not the cheapest framework
Hono's Run 1 was the cheapest single number in the benchmark at $1.55, which is the kind of number that ends up on a slide as proof that the lightweight framework wins. The cost only stayed cheap until the test suite started probing for production-readiness, at which point Hono finished Run 3 at 29 of 36 checks with tracing broken. The total cost across all three runs is a better measure of what a team would actually spend over a quarter than any individual run.
What a monthly bill looks like
A team that lets an AI agent drive most backend changes will run something like this benchmark, in shape, every working day. At per-run differences of a few dollars, the gap between the cheapest and most expensive framework projects to hundreds of dollars per engineer per month, before you factor in the cost of fixing the production issues that the more expensive framework leaves behind.
How to set up the cheapest stack
encore app create my-app
cd my-app
encore llm-rules init # CLAUDE.md
encore mcp start # MCP server
claude
Reproduce the numbers
Clone the repo, run the benchmark on your own infrastructure, or recompute against a different model: github.com/encoredev/ai-backend-benchmark.