Yesterday at work, I found myself in a hellhole of test coverage.
You know the drill—writing unit tests for utility functions. I had already covered 80% with the help of some regular AI models. But then I got told to push it to 100% coverage.
Shit. I hate this part.
The Test Coverage Grind
Completing 100% test coverage is no joke, even if you’re using the smartest LLMs available for free.
I spent hours battling edge cases, making sure every branch, condition, and scenario was covered. My test file grew to 1000+ lines.
DeepSeek R1 vs ChatGPT o3-mini: The Showdown
At first, I was using DeepSeek R1—a free reasoning model. It was… okay. It helped, but it still needed multiple attempts to get things right.
Then I switched to ChatGPT o3-mini.
👀 HOLY. SHIT. 👀
- Faster? ✅ Yep. Feels instant.
- More precise? ✅ Hell yes. No second attempts needed.
- Less hallucinations? ✅ Much more reliable.
First attempt—boom, got the correct test case.
The Refactor Test
After getting 100% coverage, I thought: “This test file is bloated as hell.”
So I asked o3-mini to refactor it.
✅ From 1000 lines → 600 lines
✅ Still 100% test coverage
Then I thought, “Wait, did I lose any edge cases?”
So I ran o3-mini again and told it to restore anything important.
✅ Final result: 600 lines, still full coverage.
Final Verdict?
🚀 ChatGPT o3-mini absolutely destroyed DeepSeek R1.
Not even close. Might be o1 vs r1 too, but I didn’t test that one yet.
What’s Your Experience?
Have you tested different LLMs for coding yet? What’s your go-to model for free AI coding assistance?
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