Replacing Junior Devs with GPT-4 Turbo? I Ran the Numbers So You Don’t Have To

“Will AI take my job?”

I get this question a lot — especially from college students, fresh grads, and junior developers trying to make sense of the current tech chaos. And I get it. With AI tools seemingly writing full apps, generating tests, and even fixing bugs, it’s fair to wonder where humans fit in.

I usually tell them this:

The industry is changing — faster than ever. But we’re not just replacing coders with machines. We’re shifting from “who can type the fastest” to “who can think the clearest.”

Still, there’s a popular narrative floating around that AI is already cheaper than hiring juniors . So I decided to put that to the test.

This article breaks down what it actually costs to use GPT-4 Turbo as a dev replacement, what it can do well, where it fails hard — and why, for now, hiring a junior dev might still be the smarter (and cheaper) choice.

Let’s dig in.

What does GPT-4 actually cost?

If you’re using GPT-4 Turbo via OpenRouter:

• Inputs cost around ₹0.8 per 1K tokens

• Outputs are ~₹2.5 per 1K tokens

• A full day of coding — with file context, testing, refactors — easily burns 1.5 to 2 million tokens
  That’s ₹400–₹600 a day, or about ₹15K–₹18K a month.

That’s not pocket change. It’s in the same ballpark as hiring a fresher or junior dev in India (₹20K–₹40K/month range).

Where AI shines

• Cranking out boilerplate 10× faster

• Refactoring, filling in gaps, documenting code

• Debugging tricky integration issues (faster than Googling)

• Writing test cases, SQL schemas, migration scripts

Where AI still falls short

• It forgets your context quickly — unless you keep spoon-feeding it

• Doesn’t get domain-specific logic unless you tell it exactly

• Can’t do standups, demos, or talk to customers

• And it definitely won’t figure out “what’s next” in a roadmap

So… is AI cheaper than a junior dev?
Only if:

• You already know what to build and how

• Your workload is predictable and low on creativity

• You’re okay spending tokens to move fast

For most startups? A junior dev is still cheaper and easier to manage. Unless:

• Your codebase is heavily templated

• You’re not tied to any specific language

• And there’s a senior dev guiding the show

Side Note #1: why GPT-4 Turbo and no other LLMs

Before settling on GPT-4 Turbo, we did experiment with a few cheaper paths. Spoiler: they didn’t quite work out. But here’s what we learned — in case you’re thinking the same.

Option 1: “Just Use GPT-3.5 Turbo, It’s Cheaper!”

Yup, it is cheaper.

But here’s the catch:
GPT-3.5 is great for quick tasks — like writing boilerplate, filling out functions, or summarizing files. But the moment your prompt gets complex, or spans multiple files, or needs subtle logic — it stumbles. Hard.

You end up rewriting, prompting again, or worse, switching models mid-way.

Option 2: “Use GPT-3.5 Most of the Time, Escalate to GPT-4 When Needed”

This sounded perfect on paper.

Why it backfired:
You’re not just paying for compute. You’re paying for time. By the time GPT-3.5 fails and you realize you need GPT-4, you’ve already lost context, time, and tokens. And often, you re-prompt from scratch.

Net result? You spend more, and your flow breaks.

What Actually Worked: Full GPT-4 Turbo

Side Note #2: What if we consider US / UK market instead of India

Let’s run the same math for US and UK junior devs, using the same token usage assumptions (1.5M–2M tokens/day) and current GPT-4 Turbo pricing via OpenRouter as of June 2025.

Estimated Monthly Cost for GPT-4 Turbo as Dev in India

Junior Dev Salaries — USA

Junior Dev Salaries — UK

Final Thoughts: It’s Not AI vs Junior Devs

It’s tempting to line up token costs next to salaries and do the math. But honestly, that’s the wrong comparison to focus on.

AI isn’t here to replace junior developers. AI is best thought of as a force multiplier. It helps the people who already know what they’re doing move faster, build better, and think clearer. It’s not a magic wand. It’s a power tool. So the real productivity unlock is pairing smart dev (like you) with:

• A GPT-4 Turbo for heavy lifting achieving speed

• A Deepseek Coder ( or any free model which we did not consider in our maths for this article) for scaffolding and structure.

• And the human devs doing the heavy lifting in terms of system thinking, validation.

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