Code fix · 4 checks · max 600 tokens · benched 2026-09-16

Kimi K3 vs Kimi K2.7 Code vs Kimi K2.6 vs Kimi K2.5 on parameterise a sql query in python

Moonshotai models side by side on "Parameterise a SQL query in Python": Kimi K2.5 scores 10/10; Kimi K2.5 is the cheapest answer scoring 8+ at $0.56 per 1,000 runs. Outputs, checks, judge reasons, latency and cost.

The prompt every model received

System

You are a senior engineer. Reply with code only unless asked otherwise.

User

This sqlite3 code is vulnerable to SQL injection. Rewrite it to use a parameterised query with sqlite3's ? placeholder. Return the complete corrected function only.

def find_user(cursor, email):
    query = f"SELECT id, name FROM users WHERE email = '{email}'"
    cursor.execute(query)
    return cursor.fetchone()

Rubric for the judge: Uses execute(sql, (email,)) with a ? placeholder, keeps the same columns and return, no string formatting left.

Side by side

Every cell is one OpenRouter call at temperature 0 with the prompt's token cap and reasoning effort "low" where the model supports it. Cost is usage × the catalogue rate in models.json. Quality is one judge call to anthropic/claude-haiku-4.5 against the prompt's rubric, cached per prompt version.

Kimi K3

moonshotai/kimi-k3

10/10

Latency: 1.2s
Cost: $0.00068
Per 1,000: $0.68

179 in · 55 out (3 reasoning) · 20 words · checks 3/4

contains
regex
not_contains
not_contains

```python
def find_user(cursor, email):
    query = "SELECT id, name FROM users WHERE email = ?"
    cursor.execute(query, (email,))
    return cursor.fetchone()
```

Judge: The output correctly uses parameterised query with ? placeholder, execute(query, (email,)) syntax, maintains identical SELECT columns and return statement, eliminates all string formatting, and provides only the corrected function as requested.

Kimi K2.7 Code

moonshotai/kimi-k2.7-code

10/10

Latency: 337ms
Cost: $0.00062
Per 1,000: $0.62

94 in · 159 out (145 reasoning) · 20 words · checks 3/4

contains
regex
not_contains
not_contains

 ```python
def find_user(cursor, email):
    query = "SELECT id, name FROM users WHERE email = ?"
    cursor.execute(query, (email,))
    return cursor.fetchone()
```

Judge: The output correctly uses parameterised query with ? placeholder, execute(query, (email,)), maintains the same SELECT columns and return statement, eliminates all string formatting, and provides only the corrected function as requested.

Kimi K2.6

moonshotai/kimi-k2.6

10/10

Latency: 876ms
Cost: $0.00102
Per 1,000: $1.02

94 in · 233 out (231 reasoning) · 20 words · checks 3/4

contains
regex
not_contains
not_contains

 ```python
def find_user(cursor, email):
    query = "SELECT id, name FROM users WHERE email = ?"
    cursor.execute(query, (email,))
    return cursor.fetchone()
```

Kimi K2.5

moonshotai/kimi-k2.5

10/10

top judge scorecheapest scoring 8+

Latency: 750ms
Cost: $0.00056
Per 1,000: $0.56

94 in · 229 out (188 reasoning) · 20 words · checks 3/4

contains
regex
not_contains
not_contains

```python
def find_user(cursor, email):
    query = "SELECT id, name FROM users WHERE email = ?"
    cursor.execute(query, (email,))
    return cursor.fetchone()
```

Frequently asked

What does this prompt test?

Code fix: Uses execute(sql, (email,)) with a ? placeholder, keeps the same columns and return, no string formatting left. The deterministic checks are contains, regex, not_contains, not_contains.

Which model should I pick for this task?

If the judge's bar of 8/10 is good enough for you, Kimi K2.5 at $0.56 per 1,000 runs. If you need the top score, Kimi K2.5 at $0.56 per 1,000 runs.

Same prompt, other families

Run it yourself

Re-run this prompt on Moonshotai with your own OpenRouter key, or tweak the wording and see what changes.

Side by side

Kimi K3

Kimi K2.7 Code

Kimi K2.6

Kimi K2.5

Frequently asked

Same prompt, other families

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