Parsimony

Existing benchmarks measure solve rate and cost, but don't punish excess code, which makes a codebase harder to work with in the long term. Parsimony measures how much code AI models add.

It takes the patches that benchmarks already publish and counts coding units: syntax elements like statements, calls, comparisons, names and literals. Lines aren't counted, so cramming code isn't rewarded, and deleted code is subtracted: net units = added − removed.

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How to read this

Models are ranked by mean net units added on the tasks they solved, lowest first. "Net units added (mean)" also includes failed attempts. Solved comes from SWE-bench Verified; tests aren't rerun. Measured is how many solved attempts could be measured.

Leaderboard


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Method

Limits

Add your own benchmark

Have code-size numbers from another benchmark? Download the example file, fill in your results and open it to get the same chart and table. The file stays in your browser. Format and how to share it.


Example: check for a negative number

Both return the same result.

def has_negative(values):
    found = False
    for value in values:
        if value < 0:
            found = True
    return found
def has_negative(values):
    return any(value < 0 for value in values)