Moonshot · Open weights
Kimi K2 Thinking
Moonshot AI's distinct Kimi K2 Thinking checkpoint is a mandatory-reasoning model for long-horizon agentic workflows and multi-step tool use.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.60
- Output
- $2.50
- Cache read
- $0.15
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 98.3K
- Average output (7 days)
- 1.9K tokens
- Longer than 91% of 465 models
Side by side
Kimi K2 Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Kimi K2 ThinkingMoonshotThis model | MiMo V2.5 ThinkingxiaomiRemove | |
|---|---|---|
| Provider | Moonshot | xiaomi |
| Discovery tier | Open weights | Open weights |
| Added | Nov 6, 2025 | Jun 3, 2026 |
| Limits | ||
| Context window | 262.14K | 1.05MBest |
| Max output | 98.3K | 131.07KBest |
| Average output | 1.9K tokens | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.60 | $0.14Best |
| Output | $2.50 | $0.28Best |
| Cache read | $0.15 | $0.0028Best |
| Cache write | — | $0.00 |
| Performance | ||
| Throughput | 48.0 tok/sBest | 29.4 tok/s |
| Time to first token | 2.6 sBest | 3.8 s |
| Request success (24h) | 99.6% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 22.0Best | 21.8 |
| Coding Index | — | 56.8 |
| Math Index | 94.7 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | Yes | Yes |
| Audio input | No | Yes |
| Video input | No | Yes |
| Reasoning effort | — | none, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Kimi K2 Thinking
- MiMo V2.5 Thinking
Intelligence Index
- Kimi K2 Thinking22.0
- MiMo V2.5 Thinking21.8
Kimi K2 Thinking: Better than 53% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 56.8
Math Index
Composite of the math evaluations
- Kimi K2 Thinking: 94.7
- MiMo V2.5 Thinking: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 18.4%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 3.3%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 754 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 996 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 4.0%
AA-LCRv1.1
Reasoning across long documents
- Kimi K2 Thinking: 72.0%
- MiMo V2.5 Thinking: 73.0%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Kimi K2 Thinking: 23.8%
- MiMo V2.5 Thinking: 27.2%Top
GPQA Diamond
Graduate-level science questions
- Kimi K2 Thinking: 83.8%
- MiMo V2.5 Thinking: 84.9%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- Kimi K2 Thinking: 84.8%
- MiMo V2.5 Thinking: —
IFBench
Following precise output instructions
- Kimi K2 Thinking: 68.1%Top
- MiMo V2.5 Thinking: 67.1%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 0.0%
SciCode
Scientific computing in Python
- Kimi K2 Thinking: —
- MiMo V2.5 Thinking: 43.9%
LiveCodeBench
Recent competitive programming problems
- Kimi K2 Thinking: 85.3%
- MiMo V2.5 Thinking: —
Math
AIME 2025
Competition mathematics, 2025 problems
- Kimi K2 Thinking: 94.7%
- MiMo V2.5 Thinking: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Kimi K2 Thinking: 31.1%
- MiMo V2.5 Thinking: 41.7%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- Kimi K2 Thinking: 93.0%Top
- MiMo V2.5 Thinking: 90.6%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Kimi K2 Thinking: 72.0%
- MiMo V2.5 Thinking: 73.0%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
- 48.0 tok/s
- Faster than 36% of 250 models
- Time to first token
- 2.6 s
- Quicker than 64% of 250 models
- Prompt cache hits
- 28.9%
- About $0.47 per 1M input tokens with caching
- Request success (24h)
- 99.6%
- 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": "moonshotai/kimi-k2-thinking",
"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-k2-thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Moonshot
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