Pick a deliberately flawed code snippet (PHP, JavaScript, SQL or Python) - the server sends it IN PARALLEL to four free AI models, who review it citing line numbers, by severity and with a suggested fix (diff), and you watch it live. At the end you see how many KNOWN bugs each one found. The snippets are intentionally preset (you can't submit your own code), so this page can't be abused as an open-ended free AI proxy.
No data yet: run a comparison and cast a vote.
If you'd like to try reviewing this exact code yourself, unlimited, with your own key, here's the exact command - copy it, swap in your own key, and run it on your own machine. Your key never reaches us, this request runs directly between your machine and the provider.
AI models evaluate code through pattern recognition: they recognise problems from similar bug patterns seen in their training data (e.g. SQL injection, race conditions, off-by-one errors) - they don't actually run the code, so they infer runtime issues rather than measure them.
Querying several models in parallel is useful because models often focus on different issues - what one misses, another often catches, so comparing them gives a more reliable picture than a single opinion. The matrix shows exactly that, bug by bug.
An AI review never replaces real testing and human review: a model can confidently state something false (a hallucination) - which is why the "+ other" count is neither a merit nor a flaw: it marks remarks that are not on the known list, and each has to be judged on its own.
The intentionally buggy, pre-defined snippets (you can't submit your own code) keep the test comparable and repeatable: every model has to find the same bug in the same snippet. Deciding whether a bug was found is a keyword heuristic, so it shows a direction rather than a verdict.
This site uses Google Analytics to measure visits. This requires your consent - see the privacy policy for details. Privacy Policy