Tencent Hunyuan Models & API

Compare the Tencent Hunyuan models available on TokenHub, including Tencent Hy3, Hunyuan 3, and Hunyuan A13B. Review pricing, context, capabilities, and model IDs, then call Tencent Hunyuan, Hunyuan, and HY3 through one OpenAI-compatible API workflow.

Tencent Hunyuan Models & API Pricing

Compare current Tencent Hunyuan API pricing, input and output token costs, context windows, endpoints, and model IDs. The catalog may include Tencent Hy3, Hunyuan 3, and Hunyuan A13B; availability follows the live TokenHub model list.

Compare input, output, and cache-read prices for the available Tencent Hunyuan models. Open a model page to confirm the current billing unit and model ID.

モデル名入力/ 百万トークン出力/ 百万トークンキャッシュ読み取り/ 百万トークン

Tencent

Hy3hy3
$0.1429$0.5714$0.0357

Compare context windows, maximum output, reasoning, tool calling, endpoints, and release dates across Tencent Hy3, Hunyuan 3, and Hunyuan A13B.

モデル名モダリティコンテキストウィンドウMax outputReasoningTool callingEndpointリリース日

Tencent

Hy3hy3
256K
128K
Anthropic / OpenAI / Responses
2026年7月6日
Catalog data

Pricing, model availability, context windows, and endpoint support reflect the current TokenHub catalog. Confirm the model detail page before a production release because specifications and availability can change.

Last updated: 2026-08-25

Get Started With the Tencent Hunyuan API

Create a TokenHub API key, copy a published Tencent Hunyuan model ID, and call it with OpenAI Chat Completions, Responses, or Claude Messages. Existing OpenAI SDK projects can usually switch by changing the API key, Base URL, and model ID.

  1. 01Create a TokenHub API key
  2. 02Choose an available Tencent Hunyuan model
  3. 03Choose an API protocol
  4. 04Copy the published Tencent Hunyuan model ID
  5. 05Send your first request

Choose an API protocol

import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.TOKENHUB_API_KEY,
  baseURL: "https://us-api.tokenhub.com/v1",
})

const result = await client.chat.completions.create({
  "model": "hy3",
  "messages": [
    {
      "role": "user",
      "content": "Explain why low latency matters for an AI product in one sentence."
    }
  ]
})
console.log(result.choices[0]?.message?.content)
import json
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("TOKENHUB_API_KEY"),
    base_url="https://us-api.tokenhub.com/v1",
)

request = json.loads("{\"model\":\"hy3\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}")
result = client.chat.completions.create(**request)
print(result.choices[0].message.content)
curl 'https://us-api.tokenhub.com/v1/chat/completions' \
  -X 'POST' \
  -H "Authorization: Bearer $TOKENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "hy3",
  "messages": [
    {
      "role": "user",
      "content": "Explain why low latency matters for an AI product in one sentence."
    }
  ]
}'
const response = await fetch("https://us-api.tokenhub.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "hy3",
    "messages": [
      {
        "role": "user",
        "content": "Explain why low latency matters for an AI product in one sentence."
      }
    ]
  }),
})
const data = await response.json()
console.log(data)
import os
import requests

response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/chat/completions",
    headers={
        "Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=__import__("json").loads("{\"model\":\"hy3\",\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}"),
)
response.raise_for_status()
print(response.json())
import OpenAI from "openai"

const client = new OpenAI({
  apiKey: process.env.TOKENHUB_API_KEY,
  baseURL: "https://us-api.tokenhub.com/v1",
})

const result = await client.responses.create({
  "model": "hy3",
  "input": "Explain why low latency matters for an AI product in one sentence."
})
console.log(result.output_text)
import json
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("TOKENHUB_API_KEY"),
    base_url="https://us-api.tokenhub.com/v1",
)

request = json.loads("{\"model\":\"hy3\",\"input\":\"Explain why low latency matters for an AI product in one sentence.\"}")
result = client.responses.create(**request)
print(result.output_text)
curl 'https://us-api.tokenhub.com/v1/responses' \
  -X 'POST' \
  -H "Authorization: Bearer $TOKENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "hy3",
  "input": "Explain why low latency matters for an AI product in one sentence."
}'
const response = await fetch("https://us-api.tokenhub.com/v1/responses", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "hy3",
    "input": "Explain why low latency matters for an AI product in one sentence."
  }),
})
const data = await response.json()
console.log(data)
import os
import requests

response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/responses",
    headers={
        "Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=__import__("json").loads("{\"model\":\"hy3\",\"input\":\"Explain why low latency matters for an AI product in one sentence.\"}"),
)
response.raise_for_status()
print(response.json())
curl 'https://us-api.tokenhub.com/v1/messages' \
  -X 'POST' \
  -H "Authorization: Bearer $TOKENHUB_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "hy3",
  "max_tokens": 1024,
  "messages": [
    {
      "role": "user",
      "content": "Explain why low latency matters for an AI product in one sentence."
    }
  ]
}'
const response = await fetch("https://us-api.tokenhub.com/v1/messages", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.TOKENHUB_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "hy3",
    "max_tokens": 1024,
    "messages": [
      {
        "role": "user",
        "content": "Explain why low latency matters for an AI product in one sentence."
      }
    ]
  }),
})
const data = await response.json()
console.log(data)
import os
import requests

response = requests.request(method="POST", url="https://us-api.tokenhub.com/v1/messages",
    headers={
        "Authorization": f"Bearer {os.environ['TOKENHUB_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=__import__("json").loads("{\"model\":\"hy3\",\"max_tokens\":1024,\"messages\":[{\"role\":\"user\",\"content\":\"Explain why low latency matters for an AI product in one sentence.\"}]}"),
)
response.raise_for_status()
print(response.json())

Which Tencent Hunyuan Model Should You Choose?

Use this Tencent Hunyuan model selection guide for Chinese-language applications, general chat, reasoning, coding, and long-context processing. Compare price, context, reasoning, tool calling, and endpoint support before shipping.

API workloadStart withWhen it fitsVerify before launch
High-volume Tencent Hunyuan API callsHy3Fast iteration, chat, extraction, summarization, and batch workloads using Tencent Hunyuan.Tencent Hunyuan API pricing, throughput, and output-token cost
Tencent Hunyuan reasoning and codingHy3Multi-step analysis, code generation, debugging, and agent tasks where answer quality matters.Reasoning support, tool calling, latency, and total request cost
General Tencent Hunyuan applicationsHy3Everyday assistants, content generation, information extraction, and product features.Task accuracy, endpoint support, and production price
Long-context Tencent Hunyuan workloadsHy3Documents, codebases, research, and conversations where input length is the constraint.Context window, input-token price, maximum output, and streaming
Quality-first Tencent Hunyuan workloadsHy3Production outputs where capability matters more than the lowest unit cost.Task quality, latency, and the price difference versus a faster model

Tencent Hunyuan API FAQ

What are Tencent Hunyuan, Hunyuan, and HY3?

Tencent Hunyuan, Hunyuan, and HY3 are names and search terms associated with this model family. TokenHub uses the published provider and model IDs shown in the live catalog.

Which Tencent Hunyuan models are available on TokenHub?

The live list above shows current availability. Relevant model searches include Tencent Hy3, Hunyuan 3, and Hunyuan A13B, but only models displayed in the TokenHub catalog can be called through this page.

How do I get a Tencent Hunyuan API key?

Tencent Hunyuan API and Tencent Hunyuan API key searches lead to the same TokenHub workflow: create an API key, select a published Tencent Hunyuan model ID, and use the TokenHub Base URL in your application.

How is Tencent Hunyuan API pricing calculated?

Pricing depends on the selected model and billing type. Compare input, output, cache, or per-request prices in the table and confirm the model detail page before production use.

Can I use the OpenAI SDK with Tencent Hunyuan?

Yes. Use the TokenHub Base URL, API key, and published Tencent Hunyuan model ID with the OpenAI Python or Node.js SDK. Endpoint support is shown for each model.

Which Tencent Hunyuan model should I use?

Choose based on the workload: Chinese-language applications, general chat, reasoning, coding, and long-context processing. Compare actual price, context, reasoning, tool calling, and output limits in the live catalog.

Does this page include every Tencent Hunyuan modality?

Hunyuan 3D, Hunyuan Video, and Hunyuan Image searches have different model and endpoint requirements from the LLM models on this page.

Start Building With Tencent Hunyuan

Choose a Tencent Hunyuan model, copy its model ID, create a TokenHub API key, and send your first request through one compatible API workflow.