Moonshot AI: Kimi K2 Instruct
moonshotai/kimi-k2-instruct
Access Kimi K2 Instruct 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-instruct"
}).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-instruct"
}).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-instruct",
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-instruct",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Kimi K2 Instruct is the instruction-tuned version of Moonshot AI's Kimi K2, released in July 2025 as a general-purpose chat and agentic model. Moonshot describes it as reflex-grade, meaning it answers directly without extended thinking, which keeps latency low in tool-calling loops.
It scores 65.8% on SWE-bench Verified with agentic tools (single attempt), 70.6% on Tau2-bench retail, and 76.5% on AceBench, close to Claude 4 on tool-use benchmarks at the time of release. Tool calling is built in; you pass a list of available tools and the model decides when and how to invoke them.
This route offers a 128K context window. It suits developers building agents, coding assistants, and multi-step tool pipelines that need autonomous execution without chain-of-thought token overhead.
Context Window 128K
tokens
Max Output 66K
tokens
Input Cost $0.7
per million tokens
Output Cost $2.5
per million tokens
Tool Use Yes
Release Date Jul 11, 2025
Model Playground
Try Kimi K2 Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Moonshot AI
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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.
ChatKimi K2.7 Code Fast
Kimi K2.7 Code Fast is the high-speed serving tier of Kimi K2.7 Code, Moonshot AI's coding-agent model. The weights and capabilities are the same as the standard route; the difference is throughput. Moonshot reports around 180 tokens per second on coding tasks with median-length inputs and up to 260 tokens per second on shorter-context tasks, up to 6x faster than the standard release. Like the base model, it runs in always-on thinking mode with a 262K-token context window and supports tool calling for agentic workflows. Compared with K2.6, K2.7 Code improves coding and agent performance while using roughly 30% fewer thinking tokens. The fast route costs about twice as much per token as the standard endpoint, so it fits interactive coding agents and IDE assistants where response speed matters more than cost.
ChatKimi K2.7 Code
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.
Frequently Asked Questions
You can access Kimi K2 Instruct 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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Kimi K2 Instruct to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.7 |
| Output | $2.5 |
Kimi K2 Instruct was created by Moonshot AI and released on Jul 11, 2025.
Kimi K2 Instruct supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
Kimi K2 Instruct can generate up to 66K tokens in a single response.
Yes, Kimi K2 Instruct supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Yes — the Kimi K2 Instruct 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 Instruct to your app without worrying about API keys or setup.
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