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Kimi K2.7 Code TEE

Added Aug 15, 2026Open weights

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Use in the app

Kimi K2.7 Code is Moonshot AI's coding-focused agentic model built for long-horizon software engineering workflows. It supports native image input, tool calling, and forced thinking mode while running inside a Trusted Execution Environment (TEE) with attestation support.

  • Reasoning
  • Tools
  • Vision
  • Parallel tools
Input
Text, Images
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.95
Output
$4.00
Cache read
$0.19

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
65.5K
Average output (7 days)
1.1K tokens
Longer than 75% of 473 models

Side by side

Kimi K2.7 Code TEE compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Kimi K2.7 Code TEEMoonshotThis modelKimi K3.1 ProMoonshotRemove
ProviderMoonshotMoonshot
Discovery tierOpen weightsFrontier
AddedAug 15, 2026Oct 24, 2026
Limits
Context window262.14K1.05MBest
Max output65.54K—
Average output1.1K tokens921 tokens
Pricing, USD per 1M tokens
Input$0.95Best$2.00
Output$4.00Best$10.00
Cache read$0.19Best$0.20
Cache write—$2.00
Performance
Throughput—53.4 tok/s
Time to first token—6.3 s
Request success (24h)—83.3%
Benchmark indexes
Intelligence Index25.855.1Best
Coding Index60.8—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputNoYes
Video inputNoYes
Parallel toolsYesNo
Reasoning effort—low, high, max

Public evaluations

Benchmarks

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

  • Kimi K2.7 Code TEE
  • Kimi K3.1 Pro

Intelligence Index

  • Kimi K2.7 Code TEE25.8
  • Kimi K3.1 Pro55.1

Kimi K2.7 Code TEE: Better than 63% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Kimi K2.7 Code TEE: 60.8
    • Kimi K3.1 Pro: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Kimi K2.7 Code TEE: 24.5%
    • Kimi K3.1 Pro: 73.3%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Kimi K2.7 Code TEE: 4.7%
    • Kimi K3.1 Pro: 46.0%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Kimi K2.7 Code TEE: 858 Elo
    • Kimi K3.1 Pro: 1,678 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Kimi K2.7 Code TEE: 1,038 Elo
    • Kimi K3.1 Pro: 1,846 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Kimi K2.7 Code TEE: 11.2%
    • Kimi K3.1 Pro: 31.4%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • Kimi K2.7 Code TEE: 79.3%
    • Kimi K3.1 Pro: 86.3%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • Kimi K2.7 Code TEE: 12.2%
    • Kimi K3.1 Pro: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Kimi K2.7 Code TEE: 35.0%
    • Kimi K3.1 Pro: 52.5%Top

  • GPQA Diamond

    Graduate-level science questions

    • Kimi K2.7 Code TEE: 89.6%
    • Kimi K3.1 Pro: —

  • IFBench

    Following precise output instructions

    • Kimi K2.7 Code TEE: 63.1%
    • Kimi K3.1 Pro: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Kimi K2.7 Code TEE: 1.0%
    • Kimi K3.1 Pro: 67.2%Top

  • SciCode

    Scientific computing in Python

    • Kimi K2.7 Code TEE: 47.8%
    • Kimi K3.1 Pro: 60.8%Top

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Kimi K2.7 Code TEE: 44.7%
    • Kimi K3.1 Pro: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Kimi K2.7 Code TEE: 90.1%
    • Kimi K3.1 Pro: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Kimi K2.7 Code TEE: 79.3%
    • Kimi K3.1 Pro: 86.3%Top

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

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": "TEE/kimi-k2.7-code",
    "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="TEE/kimi-k2.7-code",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Moonshot

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