Moonshot AI: Kimi K3.1 Pro HighSpeed
moonshotai/kimi-k3.1-pro-highspeed
Try Kimi K3.1 Pro HighSpeed for free in your browser, and add it to your app for free with Puter.js AI API.
Try it free Add to your app// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "moonshotai/kimi-k3.1-pro-highspeed"
}).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-k3.1-pro-highspeed"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
Model Card
Kimi K3.1 Pro HighSpeed is the faster-serving variant of Kimi K3.1 Pro, the multimodal language model from Moonshot AI announced in October 2026. It accepts text, image, and video input and has a 1-million-token context window.
Moonshot says it delivers the same model capabilities as Kimi K3.1 Pro at 2 to 3 times the output speed, for more responsive interactions. It is priced at twice the standard model's rate.
Choose it when latency matters more than cost, such as interactive coding agents, tool-calling loops with many sequential steps, and chat or document analysis features where users wait on the response. For batch or background jobs, the standard Kimi K3.1 Pro costs less.
Context Window 1M
tokens
Max Output 944K
tokens
Input Cost $4
per million tokens
Output Cost $20
per million tokens
Input text, image, video
modalities
Tool Use Yes
Release Date Oct 23, 2026
Try Kimi K3.1 Pro HighSpeed for free
Try Kimi K3.1 Pro HighSpeed instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
More AI Models From Moonshot AI
Find other Moonshot AI models →
Kimi K3.1 Pro
Kimi K3.1 Pro is a multimodal language model from Moonshot AI, announced October 23, 2026 as a post-trained upgrade of Kimi K3. It accepts text, image, and video input, has a 1-million-token context window, and Moonshot plans to release the weights by November 4. Moonshot reports 65.7% on Terminal-Bench 4.0, ahead of GPT-6 Astra and slightly behind Claude Opus 5.5, and 92.7% on BenchCAD, a 3D model coding benchmark. It also reports higher scores than both models on OfficeQA Pro v2, a financial analysis benchmark. Cybersecurity benchmark scores trail both, since Moonshot removed cybersecurity content from post-training data. It suits developers building coding agents, tool-calling pipelines, and financial or document analysis workflows that need long context and multimodal input.
ChatKimi 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
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 K3.1 Pro HighSpeed 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.
Kimi K3.1 Pro HighSpeed is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.
Kimi K3.1 Pro HighSpeed is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.
| Price per 1M tokens | |
|---|---|
| Input | $4 |
| Output | $20 |
Kimi K3.1 Pro HighSpeed was created by Moonshot AI and released on Oct 23, 2026.
Kimi K3.1 Pro HighSpeed supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,097 pages of text.
Kimi K3.1 Pro HighSpeed can generate up to 944K tokens in a single response.
Kimi K3.1 Pro HighSpeed accepts the following input types: text, image, video. It produces: text.
Yes, Kimi K3.1 Pro HighSpeed 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 K3.1 Pro HighSpeed 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.
Add Kimi K3.1 Pro HighSpeed to your app for free
Developers can integrate Kimi K3.1 Pro HighSpeed for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.