Hy4 | Tencent Multimodal LLM API Pricing

Name: Hy4 API
Brand: tencent
Price: 0.834 USD
Availability: InStock

tencent/hy4

Data di rilascio: 2026-11-04

1,048,576 context · $0.83/M input tokens · $2.50/M output tokens

The official release of Hy4 delivers comprehensive and substantial improvements over Hy4 Preview, with particularly strong gains in agentic capabilities and performance across a wide range of long-horizon, real-world productivity...

Prezzi

Pay-per-use

Nessun costo iniziale, paga solo per ciò che usi

Input$0.83 / M Tokens

Output$2.50 / M Tokens

Cache Read$0.04 / M Tokens

Prova il modello

tencent/hy4

Online

Ciao! Sono un assistente IA utile. Come posso aiutarti?

Pronto a usare questo modello in un coding agent locale?Setup agent

Utilizzo API

Usa i seguenti esempi di codice per integrare la nostra API:

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'tencent/hy4',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 0,
});

try {
  const response = await client.chat.completions.create({
    model: 'tencent/hy4',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  const body = response as typeof response & { error?: { message?: string } };
  if (body.error) throw new Error(body.error.message || 'LLM generation failed');
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Introduzione al modello

Tencent: Hy4

This model is available through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.

Why It Looks Great

text+image->text architecture for Text, Image to Text workloads
1048576 context window for long prompts, document analysis, and multi-turn workflows
Vision input support for image understanding and multimodal tasks
Function calling and tool-use support for agentic application workflows
Structured output support for JSON responses and schema-constrained generation
Reasoning controls available through supported parameters

Key Features

Context Window: 1048576 tokens
Max Input: 983040 tokens
Max Output: 65536 tokens
Vision: Supported
Function Calling: Supported
Structured Outputs: Supported
Image Generation: Not listed
Audio Input: Not listed
Supported Parameters: include_reasoning, max_completion_tokens, max_tokens, reasoning, reasoning_effort, response_format, stop, structured_outputs, temperature, tool_choice, tools

Specifications

Specification	Value
Provider	tencent
Model Type	Chat Completions model
Architecture	text+image->text
Context Window	1048576 tokens
Max Input	983040 tokens
Max Output	65536 tokens
Input	Text, Image
Output	Text
Vision	Supported
Function Calling	Supported
Structured Outputs	Supported
Release Date	November 4, 2026

How to Use

Write your prompt - describe the task, provide context, and specify the desired output format.
Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: tencent/hy4

API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="tencent/hy4",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "tencent/hy4",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: tencent/hy4
Provider: tencent

Info

Providertencent

Tipollm

Funzionalità supportate

Input

TestoImmagine

Output

Testo

Contesto1,048,576

Output massimo65,536

Vision✓ Supportato

Function Calling✓ Supportato

Guida all'accesso API

Base URLhttps://llm.wavespeed.ai/v1

API Endpointchat/completions

ID modellotencent/hy4

Domande frequenti su Hy4

Quanto costa Hy4 via API?+

Prezzi su WaveSpeedAI: $0.83 per milione di token in input e $2.50 per milione di token in output. Prompt caching e batch processing sono fatturati separatamente e riducono il costo effettivo su carichi lunghi e ripetitivi.

Qual è la context window di Hy4?+

Hy4 supporta fino a 1049K token di contesto e fino a 66K token di output per richiesta.

Hy4 è compatibile con OpenAI?+

WaveSpeedAI espone Hy4 su https://llm.wavespeed.ai/v1 tramite l’interfaccia Chat Completions compatibile con OpenAI. Per la maggior parte dei client OpenAI SDK basta cambiare base URL e API key; i campi opzionali dipendono dal modello.

Come si inizia con Hy4?+

Accedi a WaveSpeedAI, crea una API key in Access Keys e invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. Consulta il catalogo attuale per disponibilità, funzionalità e prezzi.