Tencent

Tencent: Hunyuan A13B Instruct

tencent/hunyuan-a13b-instruct

Access Hunyuan A13B Instruct from Tencent 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: "tencent/hunyuan-a13b-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: "tencent/hunyuan-a13b-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="tencent/hunyuan-a13b-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": "tencent/hunyuan-a13b-instruct",
    "messages": [
      {"role": "user", "content": "Explain quantum computing in simple terms"}
    ]
  }'

Model Card

Hunyuan A13B Instruct is an open-source large language model from Tencent built on a fine-grained Mixture-of-Experts (MoE) architecture, with 80B total parameters and 13B active during inference. It natively supports a 256K-token context window.

It performs competitively with OpenAI o1 and DeepSeek R1 across math, science, and reasoning benchmarks, scoring 87.3 on AIME 2024, 89.1 on BBH, and 84.7 on ZebraLogic.

Hunyuan A13B particularly excels at agentic tasks and tool use, leading on benchmarks like BFCL-v3 (78.3) and ComplexFuncBench (61.2). It's a strong choice for developers building agent workflows, long-context applications, or cost-sensitive reasoning pipelines.

Context Window 131K

tokens

Max Output 131K

tokens

Input Cost $0.14

per million tokens

Output Cost $0.57

per million tokens

Release Date Jun 27, 2025

 

Model Playground

Try Hunyuan A13B Instruct instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat tencent/hunyuan-a13b-instruct
Tencent
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Frequently Asked Questions

How do I use Hunyuan A13B Instruct?

You can access Hunyuan A13B Instruct by Tencent 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 Hunyuan A13B Instruct free?

Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Hunyuan A13B 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.

What is the pricing for Hunyuan A13B Instruct?
Pricing for Hunyuan A13B Instruct is based on the number of input and output tokens used per request.
Price per 1M tokens
Input$0.14
Output$0.57
Who created Hunyuan A13B Instruct?

Hunyuan A13B Instruct was created by Tencent and released on Jun 27, 2025.

What is the context window of Hunyuan A13B Instruct?

Hunyuan A13B Instruct supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.

What is the max output length of Hunyuan A13B Instruct?

Hunyuan A13B Instruct can generate up to 131K tokens in a single response.

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

Yes — the Hunyuan A13B 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 Hunyuan A13B Instruct to your app without worrying about API keys or setup.

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