HiAPI
21:9 高调光宽幅 Hero 图:右侧悬浮的玻璃文档层叠与贯穿的发光光带,冰蓝、珊瑚粉与薰衣草色渐变,正面玻璃面板内蚀刻发光字母 kimi,左侧大片柔光留白;为 kimi-k3.1-pro 详情页顶部主图。

Moonshot AI

Kimi K3.1 Pro

kimi-k3.1-pro-highspeed

Moonshot AI's flagship text model, focused on document understanding and long-context text generation, suitable for research and agent tasks

Context window
1,048,576
Input
Max output
131,072 tokens
Release date
2026-10-29
Reasoning Tools Streaming Structured JSON

Pricing

kimi-k3.1-pro-highspeed /1M tokens

Specifications Unit Price
Input $4.3096
Cached input $0.2156
Output $22.5426

Overview

Overview

kimi-k3.1-pro-highspeed is a text model route in Moonshot AI's Kimi K3.1 series designed for low-latency calls. It is available through the HiAPI.ai unified interface and billed per token. It targets developer scenarios that need frequent, fast text results, such as conversational Q&A, long-document summarization, and research material organization. If your needs center on text generation and understanding and you want to minimize waiting in interactive experiences, this route is the more suitable choice in the Kimi K3.1 family.

Key Highlights

  • High-speed route for the same model — It belongs to the Kimi K3.1 family alongside kimi-k3.1-pro; the highspeed version is positioned for faster responses and suits interactive calls.
  • Direct calls via a unified interface — It is integrated through HiAPI.ai's aggregated interface, so you can use the same calling method as other platform models without integrating with the vendor separately.
  • Token-based billing — Billing is measured in tokens, making it easy to estimate costs by input and output volume and incorporate them into existing usage management processes.

Capabilities

General text generation and conversation: It handles conversational Q&A and routine text generation tasks, making it suitable as the language understanding and response layer in applications.

Long-text material processing: The Kimi series is known for long context and can be used for long-document reading, summarization, and material organization tasks.

Low-latency response route: The highspeed positioning targets interactive scenarios that require faster returns, making it suitable for call chains sensitive to response pacing.

Use Cases

  • Developers building conversational Q&A applications — Take user questions as input and get natural-language answers that can be shown directly to end users, for customer service and assistant products.
  • Researchers summarizing and organizing long documents — Input long reports or materials and produce summaries and key-point outlines for subsequent reading and secondary processing.
  • Content teams generating text drafts — Input topics or outlines and produce editable text drafts for the upstream stage of content production workflows.

Limitations and Selection Guidance

This model supports only the text modality; input and output are primarily text, and multimodal inputs such as images and video are outside this route's capabilities. It is positioned as a high-speed text route. If a task requires greater output depth or complex reasoning, choose the standard version within the same family; if image or video understanding is needed, use a model that supports multimodality. Specific context length and quotas are subject to the platform's actual parameters.

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