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Moonshot · Open weights

Kimi K2.6 TEE

Added Apr 21, 2026Open weights

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Use in the app

Kimi K2.6 is Moonshot AI's next-generation multimodal model designed for long-horizon coding and agentic orchestration. Running inside a TEE (Trusted Execution Environment), with provider attestation support.

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

Pricing

USD per 1M tokens
Input
$1.50
Output
$5.25
Cache read
$0.38

Reference prices as published by the model provider. API example

Specifications

Context window
262.1K
Max output
65.5K
Average output (7 days)
3.1K tokens
Longer than 97% of 465 models

Side by side

Kimi K2.6 TEE compared

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

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Kimi K2.6 TEEMoonshotThis modelSolar Pro 4upstageRemove
ProviderMoonshotupstage
Discovery tierOpen weightsEfficient
AddedApr 21, 2026Aug 11, 2026
Limits
Context window262.14K524.29KBest
Max output65.54K131.07KBest
Average output3.1K tokens546 tokens
Pricing, USD per 1M tokens
Input$1.50$0.03Best
Output$5.25$0.12Best
Cache read$0.38$0.006Best
Performance
Throughput—80.3 tok/s
Time to first token—2.4 s
Request success (24h)100.0%Best99.9%
Benchmark indexes
Intelligence Index27.0Best26.6
Coding Index61.8—
Capabilities
ToolsYesYes
VisionYesNo
Structured outputNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • Kimi K2.6 TEE
  • Solar Pro 4

Intelligence Index

  • Kimi K2.6 TEE27.0
  • Solar Pro 426.6

Kimi K2.6 TEE: Better than 68% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Kimi K2.6 TEE: 61.8
    • Solar Pro 4: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Kimi K2.6 TEE: 13.0%
    • Solar Pro 4: 13.6%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Kimi K2.6 TEE: 1.8%
    • Solar Pro 4: 2.4%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Kimi K2.6 TEE: 819 Elo
    • Solar Pro 4: 1,093 EloTop

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Kimi K2.6 TEE: 1,038 Elo
    • Solar Pro 4: 1,106 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Kimi K2.6 TEE: 13.0%Top
    • Solar Pro 4: 7.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • Kimi K2.6 TEE: 81.0%Top
    • Solar Pro 4: 70.7%

  • MLCR-AA

    Long-context reasoning over medical records

    • Kimi K2.6 TEE: 11.1%
    • Solar Pro 4: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Kimi K2.6 TEE: 37.5%Top
    • Solar Pro 4: 29.8%

  • GPQA Diamond

    Graduate-level science questions

    • Kimi K2.6 TEE: 91.1%Top
    • Solar Pro 4: 89.1%

  • IFBench

    Following precise output instructions

    • Kimi K2.6 TEE: 76.0%
    • Solar Pro 4: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Kimi K2.6 TEE: 0.5%Top
    • Solar Pro 4: 0.0%

  • SciCode

    Scientific computing in Python

    • Kimi K2.6 TEE: 51.5%Top
    • Solar Pro 4: 48.0%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Kimi K2.6 TEE: 43.9%
    • Solar Pro 4: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Kimi K2.6 TEE: 95.9%
    • Solar Pro 4: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Kimi K2.6 TEE: 81.0%Top
    • Solar Pro 4: 70.7%

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
1.0%
About $1.49 per 1M input tokens with caching
Request success (24h)
100.0%
Reliable

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.

Hourly request success · last 72 hoursLowest hour 33.3%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

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-k2.6",
    "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-k2.6",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Moonshot

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