moonshotai/kimi-k2.6 🔢📝🖼️❓ → 📝
About
Moonshot AI's frontier open model, built for long-horizon coding, agent swarms, and autonomous software engineering. 1 trillion parameters, 262k context window, vision and tool use.
Example Output
Prompt:
"Write a Python function group_anagrams(words) that groups strings by their anagram equivalence class. Include a concise docstring, type hints, and a short example in an if __name__ == '__main__': block. Output just the code, no prose."
Output
from collections import defaultdict
from typing import List, Dict
def group_anagrams(words: List[str]) -> Dict[str, List[str]]:
"""Group words by their anagram equivalence class.
Returns a dictionary mapping sorted characters to the list of words
that are anagrams of each other.
"""
groups = defaultdict(list)
for word in words:
key = "".join(sorted(word))
groups[key].append(word)
return dict(groups)
if __name__ == '__main__':
words = ["eat", "tea", "tan", "ate", "nat", "bat"]
result = group_anagrams(words)
print(result)
# Example output: {'aet': ['eat', 'tea', 'ate'], 'ant': ['tan', 'nat'], 'abt': ['bat']}
Performance Metrics
3.88s
Prediction Time
3.89s
Total Time
All Input Parameters
{
"prompt": "Write a Python function `group_anagrams(words)` that groups strings by their anagram equivalence class. Include a concise docstring, type hints, and a short example in an `if __name__ == '__main__':` block. Output just the code, no prose.",
"max_tokens": 800,
"reasoning_effort": "none"
}
Input Parameters
- top_p
- Nucleus sampling probability threshold.
- prompt
- Text prompt to send to Kimi K2.6.
- max_tokens
- Maximum number of tokens to generate.
- image_input
- Optional list of images to include in the prompt. Kimi K2.6 supports vision inputs.
- temperature
- Sampling temperature. Higher values make output more random.
- system_prompt
- System prompt to guide the model's behavior.
- presence_penalty
- Penalizes new tokens based on whether they appear in the text so far.
- reasoning_effort
- How much effort the model spends reasoning before answering. Use 'none' to disable.
- frequency_penalty
- Penalizes new tokens based on their existing frequency in the text so far.
Output Schema
Output
Version Details
- Version ID
a9d565c31037ea4da7300302132940310533fd9e3ace6de17b771206759a6a42- Version Created
- April 22, 2026