Codebase work
Submit relevant files, interface constraints, and acceptance criteria, let the model analyze cross-module changes, then have your application run tests.
Overview
API
Pricing
kimi-k3.1-pro
Kimi K3.1 Pro: Long-Context Programming and Complex Reasoning
Kimi K3.1 Pro is Moonshot's flagship model, with native support for visual understanding and million-token context. It is suitable for codebase analysis, cross-document research, and tasks requiring multi-step reasoning. Use Chat Completions on Ace Data Cloud to submit messages and read usage.
MoonshotModel brand
ReasoningAlways enabled
VisionImage understanding
Keep your SDK. Connect in minutes.
Point the Base URL to api.acedata.cloud, configure your platform API key and the model ID below, and use your compatible SDK or client.
- API host
api.acedata.cloud- model
kimi-k3.1-pro
OpenAI Python SDK
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["ACEDATACLOUD_API_KEY"],
base_url="https://api.acedata.cloud/v1",
)
response = client.chat.completions.create(
model="kimi-k3.1-pro",
messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)Choose an available protocol for this model. OpenAI SDK uses a Base URL ending in /v1; Anthropic SDK uses the root URL. See each guide for protocol-specific parameters, tools and response formats.
Specifications and API
Verify the request format before selecting a model.
- Invocation ID
- kimi-k3.1-pro
- Model type
- Chat, reasoning, and visual understanding
- Official context
- Up to 1,048,576 token; actual API limits are subject to request results
- Platform API
- POST /kimi/chat/completions or a compatible Chat Completions endpoint
- Input
- Text and image_url image blocks in messages
- Output
- choices[].message, usage, and finish_reason
Suitable tasks
Provide sufficient context and verifiable objectives for complex tasks.
Research and analysis
Ask clear questions using text, charts, or screenshots, and require it to identify evidence, assumptions, and items to be verified.
Request example
First verify the API with a short message, then gradually add context.
POST /kimi/chat/completions
{"model":"kimi-k3.1-pro","messages":[{"role":"user","content":"请总结这段代码的关键风险"}],"reasoning_effort":"low"}The model always has reasoning enabled. Reasoning effort can be set to low, high, or max; do not pass settings that disable reasoning. For image input, use image_url content blocks in messages.
Read and verify results
Treat model output as analysis that needs to be verified.
- Read the main text from choices[].message.content; when reasoning and tool-call fields appear, retain the complete assistant message in multi-turn conversations.
- Read input and output token from usage, then compare them with your account usage records.
- Generated code needs to be tested in the target environment; visual analysis should be checked against the original image to verify key details.
Pricing and Caching
Costs depend on actual token usage and the purchased Credit plan.
View the current input, output, and cache hit prices in the Pricing card in the model catalog. Long conversations should limit the history messages sent; cache hits and writes are subject to actual usage fields and billing.
Usage Limits
Understand the division of responsibilities between model capabilities and application execution.
- One million tokens is the official model context specification and does not mean every request can reach that limit.
- Visual understanding is for analyzing images; use an image service to generate or modify images.
- The model can suggest tool calls; actual tool execution, permissions, and result verification are the responsibility of the integrating application.
Frequently Asked Questions
Quickly troubleshoot invocation and model selection issues.
Can K3.1 Pro disable reasoning?
No. This model always has reasoning enabled, with low, high, or max intensity available.
How do I send images?
Use an image_url image block in the content of messages and submit it together with the text question. First use a small image to verify the format and permissions.
Do I need to use the Responses or Messages API?
The examples on this page use Chat Completions. Before choosing another protocol, review the separate model list for that API.
How do I control costs?
Limit irrelevant history, choose an appropriate output budget, and check the Pricing card for prices for the current plan.
How do I handle multi-turn conversations and tool calls?
Save relevant message history; if the response contains reasoning_content or tool_calls, return the complete assistant message in the next turn and verify the tool results.
Use it in your favorite tools
Choose a development approach or application suited to this model and follow its setup guide.
↗Connect kimi-k3.1-pro to OpenAI SDK
OpenAI Chat Completions API
SDK installation, authentication and examples
↗Connect kimi-k3.1-pro to Cherry Studio
Using Ace Data Cloud with Cherry Studio
Chat client setup · Base URL, API key and model
↗Connect kimi-k3.1-pro to ChatBox
Using Ace Data Cloud with ChatBox
Chat client setup · Base URL, API key and model
↗Kimi Chat Completions API
API parameters and request examplesQuickstart
Try the API
API Key
Please obtain an API Key first
This is only a basic call example. See the full docs for more parameters and advanced usage.
View Docs