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Moonshot · Open weights

Kimi K2 Instruct

Added Jan 1, 2024Open weights

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Use in the app

Kimi K2 0905. Kimi-k2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1 trillion total parameters and 32 billion activated parameters. In benchmark evaluations covering general knowledge reasoning, programming, mathematics, and agent-related tasks, the K2 model outperforms other leading open-source models. Quantized at FP8.

  • Tools
  • Structured output
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.40
Output
$1.80

Reference prices as published by the model provider. API example

Specifications

Context window
256K
Max output
8.2K
Average output (7 days)
564 tokens
Longer than 54% of 473 models

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TryGPT 4.1Nvidia Nemotron 3 Super 120BGLM 4.5All 3

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Intelligence Index

12.7

Better than 28% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    57.0

    Composite of the math evaluations

    Better than 51% of 118 scored models

Document reasoning

  • AA-LCRv1.1

    53.0%

    Reasoning across long documents

    Better than 32% of 309 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    7.4%

    Expert-level questions across academic fields

    Better than 26% of 323 scored models

  • GPQA Diamond

    76.6%

    Graduate-level science questions

    Better than 39% of 291 scored models

  • MMLU-Pro

    82.4%

    Multi-subject knowledge and reasoning

    Better than 65% of 132 scored models

  • IFBench

    41.5%

    Following precise output instructions

    Better than 31% of 215 scored models

Coding

  • LiveCodeBench

    55.6%

    Recent competitive programming problems

    Better than 48% of 129 scored models

Math

  • AIME 2025

    57.0%

    Competition mathematics, 2025 problems

    Better than 51% of 118 scored models

  • AIME

    69.3%

    Competition mathematics

    Better than 68% of 72 scored models

  • MATH-500

    97.1%

    Competition math problems

    Better than 78% of 73 scored models

Legacy evaluations

  • Terminal-Bench Hard

    15.9%

    Earlier terminal task suite

    Better than 33% of 212 scored models

  • τ²-Bench Telecom

    61.1%

    Tool use in a customer-support simulation

    Better than 48% of 214 scored models

  • AA-LCR (unversioned)

    53.0%

    Long-context reasoning, earlier grading

    Better than 32% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
30.3%

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "moonshotai/kimi-k2-instruct",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="moonshotai/kimi-k2-instruct",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Moonshot

Other Moonshot models, starting with the same family.