Moonshot · Frontier
Kimi Latest
Always points to the newest recommended Kimi model, currently Kimi K3.1 Pro. Reasoning is always enabled. Select Kimi K3 explicitly to retain its checkpoint and pricing; K3.1 Pro Highspeed is available separately.
- Reasoning
- Tools
- Vision
- Structured output
- Video input
- Input
- Text, Images, Video
- Output
- Text
- Reasoning effort
- low · high · max
- Discovery tier
- Frontier
Pricing
USD per 1M tokens- Input
- $2.00
- Output
- $10.00
- Cache read
- $0.20
- Cache write
- $2.00
- $4.00 for a 1-hour cache
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- —
Side by side
Kimi Latest compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Kimi LatestMoonshotThis model | Kimi K3 TEEMoonshotRemove | |
|---|---|---|
| Provider | Moonshot | Moonshot |
| Discovery tier | Frontier | Open weights |
| Added | May 3, 2026 | Jul 31, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | — | 65.54K |
| Average output | — | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $2.00Best | $3.00 |
| Output | $10.00Best | $15.00 |
| Cache read | $0.20Best | $1.50 |
| Cache write | $2.00 | — |
| Performance | ||
| Throughput | 59.7 tok/sBest | 31.7 tok/s |
| Time to first token | 5.6 s | 5.0 sBest |
| Request success (24h) | 83.4% | 98.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 55.1Best | 43.6 |
| Coding Index | — | 76.2 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| Video input | Yes | No |
| 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 Latest
- Kimi K3 TEE
Intelligence Index
- Kimi Latest55.1
- Kimi K3 TEE43.6
Kimi Latest: Better than 99% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Kimi Latest: —
- Kimi K3 TEE: 76.2
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Kimi Latest: 73.3%Top
- Kimi K3 TEE: 58.3%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Kimi Latest: 46.0%Top
- Kimi K3 TEE: 24.8%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- Kimi Latest: —
- Kimi K3 TEE: 5.3%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Kimi Latest: 1,678 EloTop
- Kimi K3 TEE: 1,499 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Kimi Latest: 1,846 EloTop
- Kimi K3 TEE: 1,534 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Kimi Latest: 31.4%Top
- Kimi K3 TEE: 22.0%
AA-LCRv1.1
Reasoning across long documents
- Kimi Latest: 86.3%
- Kimi K3 TEE: 88.7%Top
MLCR-AA
Long-context reasoning over medical records
- Kimi Latest: —
- Kimi K3 TEE: 21.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Kimi Latest: 52.5%Top
- Kimi K3 TEE: 46.9%
GPQA Diamond
Graduate-level science questions
- Kimi Latest: —
- Kimi K3 TEE: 93.5%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Kimi Latest: 67.2%Top
- Kimi K3 TEE: 12.6%
SciCode
Scientific computing in Python
- Kimi Latest: 60.8%Top
- Kimi K3 TEE: 59.5%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Kimi Latest: 86.3%
- Kimi K3 TEE: 88.7%Top
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.
- Throughput
- 59.7 tok/s
- Faster than 41% of 250 models
- Time to first token
- 5.6 s
- Quicker than 29% of 250 models
- Prompt cache hits
- 96.7%
- About $0.26 per 1M input tokens with caching
- Request success (24h)
- 83.5%
- Unstable
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": "moonshotai/kimi-latest",
"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="moonshotai/kimi-latest",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Moonshot
Related models
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