Kimi K3.1 Pro

Kimi K3.1 Pro 多模态推理模型,支持 1M 上下文、文本与视觉理解、函数调用。缓存写入分 5 分钟与 1 小时计价,思考 Token 包含在输出用量中。

Model ID: kimi-k3.1-pro · Type: chat · Provider: Moonshot

Endpoints: /v1/chat/completions · /v1/messages · /v1/responses

Pricing

Input (per 1M tokens)$1.1 USD
Output (per 1M tokens)$5.5 USD
Cache read implicit (per 1M tokens)$0.11 USD
Cache read explicit (per 1M tokens)$0.11 USD
Cache write 5m (per 1M tokens)$1.1 USD
Cache write 1h (per 1M tokens)$2.2 USD

Capabilities

from openai import OpenAI

client = OpenAI(api_key="sk-...", base_url="https://api.router.ai/v1")
resp = client.chat.completions.create(
    model="kimi-k3.1-pro",
    messages=[{"role": "user", "content": "Hello"}],
)
print(resp.choices[0].message.content)

FAQ

How much does Kimi K3.1 Pro cost on 5699.ai?

Kimi K3.1 Pro (`kimi-k3.1-pro`) is billed per usage at $1.1/1M in · $5.5/1M out, in USD. Current pricing is always listed at https://5699.ai/models/kimi-k3.1-pro.

How do I call Kimi K3.1 Pro through 5699.ai?

Send a request to https://api.router.ai/v1/v1/chat/completions with the header `Authorization: Bearer <your API key>` and `"model": "kimi-k3.1-pro"`. The API is OpenAI-compatible, so any OpenAI SDK works by changing base_url to https://api.router.ai/v1 — no other code change.

Which endpoints does Kimi K3.1 Pro support?

Kimi K3.1 Pro can be called on: /v1/chat/completions; /v1/messages; /v1/responses.

What is Kimi K3.1 Pro's context window?

Kimi K3.1 Pro accepts up to 1,048,576 input tokens and can return up to 1,048,576 output tokens. Requests exceeding the input limit are rejected before reaching the model.

What can Kimi K3.1 Pro do?

Kimi K3.1 Pro supports: vision, function_calling, prompt_caching, thinking, input_video, structured_output.

Who makes Kimi K3.1 Pro?

Kimi K3.1 Pro is a chat model from Moonshot, available through the 5699.ai gateway with the same API key as every other model.

Call it through the 5699.ai OpenAI-compatible endpoint (API base: https://api.router.ai/v1). AI agents can browse the catalog and call any text model through MCP (https://mcp.router.ai/mcp); for image, video and other modalities use the API above.

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