hunyuan-a13b-instruct
Hunyuan-A13B is a mixture-of-experts language model from Tencent with 13B active out of 80B total parameters, supporting chain-of-thought reasoning.
Precio: Entrada: 33.6 créditos / 1 M de tokens (≈ $0.17); salida: 136.8 créditos / 1 M de tokens (≈ $0.68).
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Hunyuan A13B Instruct API on ModelFold
Hunyuan-A13B is a mixture-of-experts language model from Tencent with 13B active out of 80B total parameters, supporting chain-of-thought reasoning. Try Hunyuan A13B Instruct in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Hunyuan A13B Instruct API
Hunyuan A13B Instruct at a glance
Hunyuan A13B Instruct is a chat model from Tencent. It accepts text as input and returns text, with a context window of up to 131K tokens.
Use it without hosting anything
On ModelFold you call Hunyuan A13B Instruct with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Hunyuan A13B Instruct
Up to 131K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Reasoning mode
Hunyuan A13B Instruct can produce reasoning before its final answer; in the Playground you can switch reasoning on or off to compare results.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Hunyuan A13B Instruct on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Hunyuan A13B Instruct responds before writing any code.
- 2
Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "hunyuan-a13b-instruct" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Hunyuan A13B Instruct
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Writing and content
Draft, edit and translate articles, emails, product copy and documentation in a consistent tone.
Frequently Asked Questions
What is Hunyuan A13B Instruct?⌄
Hunyuan-A13B is a mixture-of-experts language model from Tencent with 13B active out of 80B total parameters, supporting chain-of-thought reasoning.
Which inputs does Hunyuan A13B Instruct support?⌄
Hunyuan A13B Instruct accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Hunyuan A13B Instruct?⌄
Up to 131K tokens, shared between your input and the model’s output.
Does Hunyuan A13B Instruct support function calling?⌄
Function calling is not listed for Hunyuan A13B Instruct; requests that include tools will be rejected. Use plain prompts or JSON output instead.
How is Hunyuan A13B Instruct billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Hunyuan A13B Instruct through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "hunyuan-a13b-instruct", using your ModelFold API key as the Bearer token.
| Entrada | 33.6 créditos 1M tokens≈ $0.17 |
| Salida | 136.8 créditos 1M tokens≈ $0.68 |
Se cobra por token, con tarifas separadas para entrada y salida. Los tokens de razonamiento cuentan como salida. El entorno de pruebas aplica exactamente el mismo cálculo.
Leer la documentación de la API →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"hunyuan-a13b-instruct","messages":[{"role":"user","content":"Hello"}]}'