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Moonshot

Chat with Kimi K2.7 Code online

Moonshot's coding specialist — a trillion parameters pointed at agents that work across files, tools and the terminal.

试用 Kimi K2.7 Code 查看方案
790,000+ 位用户的信赖

262.144K tokens

上下文窗口

131,072 tokens

最大输出

中速

速度

你会用它做什么

Agentic coding

Long runs across files, tools and terminal commands.

Large refactors

Multi-file changes that stay consistent to the end.

Debugging from evidence

Reads real error output and forms a hypothesis first.

Screenshot in, fix out

Paste a broken render and describe the fix.

Prompts to steal

Tuned to this model — click any line to copy.

关于 Kimi K2.7 Code

Kimi K2.7 Code is the coding specialist in Moonshot AI's Kimi line, released on 12 June 2026. Where Kimi K3 is the generalist you ask about anything, K2.7 Code is the one pointed at software: a one-trillion-parameter mixture-of-experts model with about 32 billion parameters active per token, built for agents that operate across files, tools and terminal commands over an extended session rather than answering a single question.

Two things define it. The first is scope: a 262,144-token context window, which is enough to hold a substantial slice of a real codebase — several files, the configuration, the docs and a long agent transcript — without chunking tricks or aggressive summarisation. The second is restraint. Moonshot reports that K2.7 Code cuts reasoning token usage by roughly 30% against K2.6 while scoring about 21.8% higher on the lab's own Kimi Code Bench v2, which is the unusual combination of thinking less and getting more right.

Thinking is always on, so the model reasons before each response and each tool call rather than waiting to be asked. In practice that shows up as fewer wrong turns in the middle of a long refactor: it reads the error, forms a hypothesis, and checks it, instead of guessing and rerunning. It takes images as input too, so a screenshot of a broken render or a failing dashboard can go straight into the conversation.

The weights are open under a Modified MIT licence, which matters if you care about being able to self-host later or audit what you are building on. On NinjaChat it is included in every plan: pick it from the model list and keep a whole engineering task in one thread.

如何使用 Kimi K2.7 Code

从零到第一个结果,不到一分钟。

01

Create a NinjaChat account and choose a plan

02

Open chat and pick Kimi K2.7 Code from the model list

03

Give it the files, the error output and the goal

04

Keep the whole task in one thread so its reasoning carries across turns

获得更好结果的技巧

  • Paste stack traces verbatim; it debugs from evidence
  • Say which files it may change and which it may not
  • Ask for a plan before a big refactor, then let it execute
  • Switch to Kimi K3 when the question is not about code

Kimi K2.7 Code 与同类模型对比

客观对比——{model} 的优势所在,以及它的不足之处。

对比 Kimi K3

查看模型

+Tuned for code and long agent runs, and cheaper

–K3 is the stronger generalist for non-coding work

对比 GPT-5.3 Codex

查看模型

+Open weights and a lower price per token

–Codex has OpenAI's tooling and reasoning-effort controls

对比 GLM 5.2

查看模型

+More token-efficient over long coding sessions

–GLM 5.2 is broader across systems design

常见问题解答

不止于对话——图像与视频

每个 NinjaChat 方案均包含 50+ 个模型、完整图像工作室和视频生成功能。

A real FLUX Pro Ultra outputA real Google Imagen 4 outputA real Seedream output
查看所有模型 →

Kimi K2.7 Code,还有另外 50 多个模型。

一个订阅即可使用 NinjaChat 上的所有模型,包括 Kimi K2.7 Code。

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更多模型,等你探索

Kimi K3

Moonshot 最新开源权重旗舰,原生视觉能力,100 万上下文

→

GPT-5.3 Codex

OpenAI's agentic coding model for real software work

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GLM 5.2

Z.ai 面向编程、智能体与系统工程的旗舰模型

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