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
Kimi K3 TEE compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Kimi K3 TEEMoonshotThis model | Kimi LatestMoonshotRemove | |
|---|---|---|
| Provider | Moonshot | Moonshot |
| Discovery tier | Open weights | Frontier |
| Added | Jul 31, 2026 | May 3, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 65.54K | — |
| Average output | 1.1K tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $3.00 | $2.00Best |
| Output | $15.00 | $10.00Best |
| Cache read | $1.50 | $0.20Best |
| Cache write | — | $2.00 |
| Performance | ||
| Throughput | 87.4 tok/sBest | 67.9 tok/s |
| Time to first token | 3.2 sBest | 4.4 s |
| Request success (24h) | 98.0%Best | 83.3% |
| Benchmark indexes | ||
| Intelligence Index | 43.6 | 55.1Best |
| Coding Index | 76.2 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| Video input | No | Yes |
| Reasoning effort | low, high, max | low, high, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Kimi K3 TEE
- Kimi Latest
Intelligence Index
- Kimi K3 TEE43.6
- Kimi Latest55.1
Kimi K3 TEE tested at max reasoning effort
Kimi K3 TEE: Better than 89% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Kimi K3 TEE: 76.2
- Kimi Latest: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Kimi K3 TEE: 58.3%
- Kimi Latest: 73.3%Top
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Kimi K3 TEE: 24.8%
- Kimi Latest: 46.0%Top
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- Kimi K3 TEE: 5.3%
- Kimi Latest: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Kimi K3 TEE: 1,499 Elo
- Kimi Latest: 1,678 EloTop
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Kimi K3 TEE: 1,534 Elo
- Kimi Latest: 1,846 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Kimi K3 TEE: 22.0%
- Kimi Latest: 31.4%Top
AA-LCRv1.1
Reasoning across long documents
- Kimi K3 TEE: 88.7%Top
- Kimi Latest: 86.3%
MLCR-AA
Long-context reasoning over medical records
- Kimi K3 TEE: 21.7%
- Kimi Latest: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Kimi K3 TEE: 46.9%
- Kimi Latest: 52.5%Top
GPQA Diamond
Graduate-level science questions
- Kimi K3 TEE: 93.5%
- Kimi Latest: —
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Kimi K3 TEE: 12.6%
- Kimi Latest: 67.2%Top
SciCode
Scientific computing in Python
- Kimi K3 TEE: 59.5%
- Kimi Latest: 60.8%Top
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Kimi K3 TEE: 88.7%Top
- Kimi Latest: 86.3%
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
- 87.4 tok/s
- Faster than 57% of 256 models
- Time to first token
- 3.2 s
- Quicker than 48% of 256 models
- Prompt cache hits
- 83.6%
- About $1.75 per 1M input tokens with caching
- Request success (24h)
- 98.0%
- 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.
- 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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