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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 fix an off-by-one in python

Moonshotai models side by side on "Fix an off-by-one in Python": Kimi K2.5 scores 10/10; Kimi K2.5 is the cheapest answer scoring 8+ at $0.59 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 function should return the arithmetic mean of a non-empty list of numbers, but its result is wrong. Fix the bug with the smallest possible change and return the complete corrected function only, in a Python code block.

def average(nums):
    total = 0
    for n in nums:
        total += n
    return total / (len(nums) - 1)

Rubric for the judge: Returns the full function with the divisor corrected to len(nums) and no other behavioural changes.

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
1.3s
Cost
$0.00109
Per 1,000
$1.09

187 in · 90 out (46 reasoning) · 18 words · checks 4/4

  • contains
  • regex
  • not_contains
  • not_contains
```python
def average(nums):
    total = 0
    for n in nums:
        total += n
    return total / len(nums)
```

Judge: The output correctly fixes the bug by changing the divisor from len(nums) - 1 to len(nums), returns the complete function in a Python code block, and makes no other changes.

Kimi K2.7 Code

moonshotai/kimi-k2.7-code

10/10
Latency
985ms
Cost
$0.00067
Per 1,000
$0.67

101 in · 171 out (137 reasoning) · 18 words · checks 4/4

  • contains
  • regex
  • not_contains
  • not_contains
```python
def average(nums):
    total = 0
    for n in nums:
        total += n
    return total / len(nums)
```

Judge: The output correctly fixes the bug by changing the divisor from len(nums) - 1 to len(nums), returns the complete function in a Python code block, and makes no other changes.

Kimi K2.6

moonshotai/kimi-k2.6

10/10
Latency
334ms
Cost
$0.00105
Per 1,000
$1.05

102 in · 238 out (211 reasoning) · 18 words · checks 4/4

  • contains
  • regex
  • not_contains
  • not_contains
 ```python
def average(nums):
    total = 0
    for n in nums:
        total += n
    return total / len(nums)
```

Judge: The output correctly fixes the bug by changing the divisor from len(nums) - 1 to len(nums), returns the complete function in a Python code block, and makes no other changes.

Kimi K2.5

moonshotai/kimi-k2.5

10/10
top judge scorecheapest scoring 8+
Latency
975ms
Cost
$0.00059
Per 1,000
$0.59

102 in · 241 out (208 reasoning) · 18 words · checks 4/4

  • contains
  • regex
  • not_contains
  • not_contains
```python
def average(nums):
    total = 0
    for n in nums:
        total += n
    return total / len(nums)
```

Judge: The output correctly fixes the bug by changing the divisor from len(nums) - 1 to len(nums), returns the complete function in a Python code block, and makes no other changes.

Frequently asked

What does this prompt test?

Code fix: Returns the full function with the divisor corrected to len(nums) and no other behavioural changes. 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 $0.59 per 1,000 runs. If you need the top score, Kimi K2.5 at $0.59 per 1,000 runs.

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