Moonshot · Open weights
Kimi K3 TEE
Kimi K3 is Moonshot AI's open-weight, always-thinking multimodal model for long-context reasoning, coding, tool use, and native image understanding. Running inside a TEE (Trusted Execution Environment), with provider attestation support.
- Reasoning
- Tools
- Vision
- Structured output
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- low · high · max
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $3.00
- Output
- $15.00
- Cache read
- $1.50
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 65.5K
- Average output (7 days)
- 1.1K tokens
- Longer than 75% of 473 models
Side by side
Compare models
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Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
Intelligence Index
43.6
Tested at max reasoning effort
Better than 89% of 326 scored models
Indexes
Coding Index
76.2Composite of the coding evaluations
Better than 91% of 168 scored models
Agentic work
AutomationBench-AA
58.3%Workflow automation, penalized for guardrail violations
Better than 75% of 173 scored models
AutomationBench-AA tasks completed
24.8%Workflows finished end to end without a guardrail violation
Better than 72% of 173 scored models
Harvey LAB-AAv1.1
5.3%Legal tasks passed in full, with no material hallucination
Better than 82% of 29 scored models
AA-Briefcasev1.1
1,499 EloAgentic knowledge work, rated head to head
Better than 83% of 166 scored models
GDPval-AAv2.1
1,534 EloEconomically valuable occupational tasks, rated head to head
Better than 80% of 187 scored models
Document reasoning
GDP.pdf
22.0%Professional reasoning over PDF documents, all-pass rate
Better than 80% of 171 scored models
AA-LCRv1.1
88.7%Reasoning across long documents
Better than 99% of 309 scored models
MLCR-AA
21.7%Long-context reasoning over medical records
Better than 84% of 121 scored models
Reasoning and knowledge
Humanity’s Last Exam
46.9%Expert-level questions across academic fields
Better than 90% of 323 scored models
GPQA Diamond
93.5%Graduate-level science questions
Better than 92% of 291 scored models
Coding
Terminal-Benchv4.0
12.6%Practical software engineering in a terminal
Better than 65% of 171 scored models
SciCode
59.5%Scientific computing in Python
Better than 92% of 174 scored models
Legacy evaluations
AA-LCR (unversioned)
88.7%Long-context reasoning, earlier grading
Better than 99% of 309 scored models
Scores from Artificial Analysis, updated Oct 26, 2026. Kimi K3 TEE was tested at max reasoning effort; compare scores measured at the same effort.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.
- Throughput
- 42.1 tok/s
- Faster than 28% of 260 models
- Time to first token
- 2.5 s
- Quicker than 67% of 260 models
- Prompt cache hits
- 84.5%
- About $1.73 per 1M input tokens with caching
- Request success (24h)
- 97.9%
- 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.
- 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.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "TEE/kimi-k3",
"reasoning_effort": "low",
"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-k3",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Moonshot
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