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Moonshot AI

Moonshot AI: Kimi K2.7 Code

moonshotai/kimi-k2.7-code

Access Kimi K2.7 Code from Moonshot AI using Puter.js AI API.

Get Started
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "moonshotai/kimi-k2.7-code"
}).then(response => {
    document.body.innerHTML = response.message.content;
});
<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "moonshotai/kimi-k2.7-code"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>
# pip install openai
from openai import OpenAI

client = OpenAI(
    base_url="https://api.puter.com/puterai/openai/v1/",
    api_key="YOUR_PUTER_AUTH_TOKEN",
)

response = client.chat.completions.create(
    model="moonshotai/kimi-k2.7-code",
    messages=[
        {"role": "user", "content": "Explain quantum computing in simple terms"}
    ],
)

print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
  -d '{
    "model": "moonshotai/kimi-k2.7-code",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Kimi K2.7 Code is Moonshot AI's open-weight coding-agent model, released June 2026 and purpose-built for long-horizon, autonomous coding tasks. It shares the same 1-trillion-parameter Mixture-of-Experts architecture (32B active parameters) as K2.6 but is entirely focused on software engineering workloads.

Compared to K2.6, it improves 21.8% on Kimi Code Bench v2, 11% on Program Bench, and 31.5% on MLS Bench Lite, while cutting reasoning-token usage by roughly 30%. It always runs in thinking mode — non-thinking mode is not supported.

With a 262K-token context window, K2.7 Code is well-suited for multi-file, repository-scale coding pipelines and agentic workflows where sustained reasoning and deep code understanding matter.

Context Window 262K

tokens

Max Output 262K

tokens

Input Cost $0.95

per million tokens

Output Cost $4

per million tokens

Input text

modalities

Tool Use Yes

 

Release Date Jun 12, 2026

 

Output Speed 36

tokens / sec

Latency 1.34s

time to first token

Model Playground

Try Kimi K2.7 Code instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat moonshotai/kimi-k2.7-code
Moonshot AI
Chat with Kimi K2.7 Code
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Benchmarks

How Kimi K2.7 Code performs on standard evaluations.

Artificial Analysis
Intelligence Index
41.9
Better than 91% of tracked models
Artificial Analysis
Coding Index
60.8
Better than 80% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
89.6%
Humanity's Last Exam Cross-domain reasoning
32.8%
SciCode Scientific programming
47.5%
IFBench Instruction following
63.1%
LCR Long-context reasoning
66.3%
Terminal-Bench Hard Agentic terminal tasks
44.7%
τ²-Bench Tool use / agents
90.1%

Scores sourced from Artificial Analysis.

Find other Moonshot AI models

Chat

Kimi K3

Kimi K3 is Moonshot AI's flagship open-weight model, released July 16, 2026, with full weights following on July 27. At roughly 2.8 trillion parameters in a Mixture-of-Experts architecture, Moonshot positions it as the largest open-source model released to date, built on two new components: Kimi Delta Attention, a hybrid linear attention mechanism, and Attention Residuals, a replacement for standard residual connections. It runs in an always-on thinking mode with a 1-million-token context window and accepts text, image, and video input. Reported results include 93.5% on GPQA Diamond, 91.2% on BrowseComp, 88.3% on Terminal-Bench 2.1, and a first-place finish on Arena.ai's Frontend Code Arena, putting it close to Claude Opus 4.8 and GPT-5.5 on several agentic and coding tasks. These figures come from Moonshot and early testers, not independently confirmed leaderboards. It suits developers building long-horizon coding agents and tool-calling pipelines who want frontier-level performance at open-weight pricing.

Chat

Kimi K2.6

Kimi K2.6 is Moonshot AI's latest open-weight multimodal model, built on a 1-trillion-parameter mixture-of-experts architecture with a 256K context window. It excels at agentic coding and long-horizon execution, supporting sustained autonomous workflows with 4,000+ tool calls across languages like Rust, Go, and Python. On key benchmarks, it scores 58.6 on SWE-Bench Pro, 54.0 on HLE with Tools, and 50.0 on Toolathlon — competitive with GPT-5.4 and Claude Opus 4.6 on coding and agent tasks, though trailing them on pure reasoning. The model accepts text, image, and video input, supports both thinking and non-thinking modes, and offers an OpenAI-compatible API. It's a strong pick for developers building multi-step agentic workflows and complex software engineering pipelines.

Chat

Kimi K2.5

Kimi K2.5 is Moonshot AI's most capable open-source model, a natively multimodal (vision + text) trillion-parameter MoE with 32B active parameters released in January 2026. Built through continual pretraining on ~15 trillion mixed visual and text tokens atop the K2 base, it supports both thinking and instant modes with a 256K context window. It scored 76.8% on SWE-bench Verified, 96.1% on AIME 2025, and 50.2% on Humanity's Last Exam with tools — outperforming Claude Opus 4.5 and GPT-5.2 on the latter. Its standout feature is Agent Swarm, which coordinates up to 100 parallel sub-agents for complex tasks. K2.5 excels at vision-to-code generation, frontend development from screenshots, and large-scale agentic workflows, making it a strong choice for developers building multimodal AI agents.

Frequently Asked Questions

How do I use Kimi K2.7 Code?

You can access Kimi K2.7 Code by Moonshot AI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Is Kimi K2.7 Code free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Kimi K2.7 Code to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.

What is the pricing for Kimi K2.7 Code?
Kimi K2.7 Code costs $0.95 per 1M input tokens and $4 per 1M output tokens.
Price per 1M tokens
Input$0.95
Output$4
Who created Kimi K2.7 Code?

Kimi K2.7 Code was created by Moonshot AI and released on Jun 12, 2026.

What is the context window of Kimi K2.7 Code?

Kimi K2.7 Code supports a context window of 262K tokens. For reference, that is roughly equivalent to 524 pages of text.

What is the max output length of Kimi K2.7 Code?

Kimi K2.7 Code can generate up to 262K tokens in a single response.

What types of input can Kimi K2.7 Code process?

Kimi K2.7 Code accepts the following input types: text. It produces: text.

Does Kimi K2.7 Code support tool use (function calling)?

Yes, Kimi K2.7 Code supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

How does Kimi K2.7 Code perform on benchmarks?

Kimi K2.7 Code scores 41.9 on the Artificial Analysis Intelligence Index, outperforming 91% of tracked models. On coding, it scores 60.8 (outperforms 80% of models).

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the Kimi K2.7 Code API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Get started with Puter.js

Add Kimi K2.7 Code to your app without worrying about API keys or setup.

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