Moonshot · Open weights
Kimi K2.6 TEE
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.
| Kimi K2.6 TEEMoonshotThis model | Kimi K2.5MoonshotRemove | |
|---|---|---|
| Provider | Moonshot | Moonshot |
| Discovery tier | Open weights | Open weights |
| Added | Apr 21, 2026 | Jan 26, 2026 |
| Limits | ||
| Context window | 262.14K | 262.14K |
| Max output | 65.54K | 65.54K |
| Average output | 3.1K tokens | 437 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $1.50 | $0.38Best |
| Output | $5.25 | $2.00Best |
| Cache read | $0.38 | $0.07Best |
| Performance | ||
| Throughput | — | 91.9 tok/s |
| Time to first token | — | 1.3 s |
| Request success (24h) | 100.0%Best | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | 27.0Best | 23.5 |
| Coding Index | 61.8Best | 46.8 |
| Capabilities | ||
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Kimi K2.6 TEE
- Kimi K2.5
Intelligence Index
- Kimi K2.6 TEE27.0
- Kimi K2.523.5
Kimi K2.6 TEE: Better than 68% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Kimi K2.6 TEE: 61.8Top
- Kimi K2.5: 46.8
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Kimi K2.6 TEE: 13.0%
- Kimi K2.5: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Kimi K2.6 TEE: 1.8%
- Kimi K2.5: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Kimi K2.6 TEE: 819 Elo
- Kimi K2.5: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Kimi K2.6 TEE: 1,038 EloTop
- Kimi K2.5: 839 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Kimi K2.6 TEE: 13.0%
- Kimi K2.5: —
AA-LCRv1.1
Reasoning across long documents
- Kimi K2.6 TEE: 81.0%Top
- Kimi K2.5: 78.0%
MLCR-AA
Long-context reasoning over medical records
- Kimi K2.6 TEE: 11.1%
- Kimi K2.5: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Kimi K2.6 TEE: 37.5%Top
- Kimi K2.5: 30.7%
GPQA Diamond
Graduate-level science questions
- Kimi K2.6 TEE: 91.1%Top
- Kimi K2.5: 87.9%
IFBench
Following precise output instructions
- Kimi K2.6 TEE: 76.0%Top
- Kimi K2.5: 70.2%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Kimi K2.6 TEE: 0.5%
- Kimi K2.5: —
SciCode
Scientific computing in Python
- Kimi K2.6 TEE: 51.5%
- Kimi K2.5: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Kimi K2.6 TEE: 43.9%Top
- Kimi K2.5: 34.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Kimi K2.6 TEE: 95.9%Top
- Kimi K2.5: 95.9%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Kimi K2.6 TEE: 81.0%Top
- Kimi K2.5: 78.0%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- Kimi K2.6 TEE
- Kimi K2.5
| Leaderboard | Kimi K2.6 TEE | Kimi K2.5 |
|---|---|---|
| SWE-bench Verified | Not in top 20 | #10 · 73.8% |
Ranks among Noumen catalog models on Epoch AI leaderboards. Only top-20 placements are listed.Epoch AI
- Kimi K2.6 TEE
- Kimi K2.5
| Leaderboard | Kimi K2.6 TEE | Kimi K2.5 |
|---|---|---|
| EQ-Bench 3 | Not in top 20 | #15 · 1530 |
Ranks among Noumen catalog models on EQ-Bench leaderboards. Only top-20 placements are listed.EQ-Bench
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.
- 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-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
Related models
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