Which Free AI Is Best for Coding? We Ran the Code Three Models Wrote

"Which AI is best for coding?" is one of the most common AI questions people type into Google, and most answers to it are opinions. We wanted evidence. On 25 October 2026 we gave the same two Python tasks to the three free models our tool uses by default — Google's Gemini 3.6 Flash, OpenAI's open-weight gpt-oss-120b (served by Groq) and Mistral's Ministral 14B — and then ran the code each one wrote against a set of test cases.

The two tasks

1. An IPv4 address checker. is_valid_ipv4(s) must accept addresses like 192.168.1.1 and reject everything else: numbers above 255, leading zeros such as 01.2.3.4, spaces, plus or minus signs, empty parts, and — we said explicitly — anything that isn't a plain ASCII digit. We tested it with 31 inputs.
2. A duration parser. parse_duration(s) turns "1h30m" into 5,400 seconds and "1h 5m 10s" into 3,910, and must raise an error for inputs like "1h1h", "30s1m" or "1.5h". We tested it with 28 inputs, including every example from the prompt.

Each model saw exactly the same prompt and was asked for code only.

The results

Only Gemini passed everything. But look at the pattern: the two models that slipped failed different tasks, and each of them wrote a completely correct solution to the other one.

Bug 1: the comment said ASCII, the code didn't

gpt-oss-120b wrote a tidy function whose own docstring promised it "Contains only ASCII digits". The check it actually used was Python's str.isdigit(), which returns True for digits in any script. So its function accepted ١.2.3.4 (written with an Arabic-Indic one) and １.2.3.4 (with a full-width one) as valid addresses. This kind of bug survives code review precisely because the comment above it sounds right.

The fix is one line: part.isascii() and part.isdigit(). Gemini compared each character with "0" <= c <= "9", and Ministral used a regular expression with [0-9], which only matches ASCII digits — both correct.

Bug 2: failing the example in the question

Ministral 14B's duration parser looked thorough. It checked for duplicate units and enforced the order h, m, s. But it split the input on spaces and then expected every piece to be a single number and unit, so "1h30m" — the very first example in our prompt — raised an error, and so did "1h10s". It also returned 0 for a string of spaces instead of rejecting it. gpt-oss and Gemini each used a single regular expression and passed all 28 cases.

What the combined answer did

For the duration task, our tool's combined answer presented Gemini's regular-expression version, which passes every test. (We didn't record the combined answer for the IPv4 task.) That helps, but it isn't a guarantee: a summary picks the approach that looks strongest; it doesn't run your tests.

So which free AI is best for coding?

In this small test, Gemini 3.6 Flash was the only model with a perfect score. But two tasks are not a benchmark, and every model here produced at least one fully correct solution. The more useful lesson is how to work with any of them:

• Run it before you trust it. A few minutes of test cases found both bugs. Reading the code didn't.
• Put your edge cases in the prompt — and still check them. Ministral failed an example we had written out for it.
• Don't trust comments. A docstring describes what the model meant to do, not what the code does.
• Ask two models and compare. Where two solutions disagree on an input, one of them is usually wrong, which is the quickest way to find the test case that matters.

Our tool does that last step for you: ask once, and the answers from several models appear side by side, each in its own copyable code block. We ran the code in Python on 25 October 2026; models can answer differently from one run to the next. For the same models on numbers rather than code, see Is AI Good at Math?