Official 0813 Pro release with major gains across coding, repository work, tool use, and agent tasks, plus hybrid thinking and a 1M context window.
DeepSeekGeneracion de texto1M contextoLanzado 13 ago 2026SingaporeEndpoint propietarioNuevoOfficial 0813 Pro release with major gains across coding, repository work, tool use, and agent tasks, plus hybrid thinking and a 1M context window.
Supports text input, hybrid thinking with enable_thinking and thinking_budget, function calling, strict JSON Schema output, and optional Linkup web search. Thinking tokens are billed as output tokens.
También conocido como DeepSeek Pro 0813, DeepSeek 0813
deepseek-v4-pro-0813/v1/chat/completionsPOST/v1/responsesPOST/v1/messagesPOST/v1beta/models/deepseek-v4-pro-0813:generateContentdeepseek/deepseek-v4-pro-0813deepseek-ai/deepseek-v4-pro-0813Tarifas de pago por uso en vivo del catálogo de EmpirioLabs. Solo pagas por lo que usas, sin mínimo mensual.
DeepSeek V4 Pro 0813 sirve la API de Chat Completions compatible con OpenAI. Apunta cualquier SDK de OpenAI a https://api.empiriolabs.ai/v1 con tu clave de API de EmpirioLabs y usa el id de modelo deepseek-v4-pro-0813. Consigue una clave de API en el panel de EmpirioLabs.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-pro-0813",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'from openai import OpenAI
client = OpenAI(
base_url="https://api.empiriolabs.ai/v1",
api_key="YOUR_EMPIRIOLABS_API_KEY",
)
response = client.chat.completions.create(
model="deepseek-v4-pro-0813",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Parámetros de solicitud compatibles con la API de DeepSeek V4 Pro 0813 en EmpirioLabs. Los valores por defecto se aplican cuando se omite un campo.
| Parámetro | Tipo | Predeterminado | Rango / valores | Descripción |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 a 2 | Sampling temperature. 0 = deterministic, 2 = maximum randomness. |
| top_p | number | 0.9 | 0 a 1 | Nucleus sampling probability mass. Lower = more focused. |
| max_tokens | number | 4096 | 1 a 393216 | Maximum output tokens. |
| stop | string | - | - | Up to 4 strings where the model will stop generating further tokens. |
| enable_thinking | boolean | true | - | Enable step-by-step reasoning before answering. |
| thinking_budget | number | 32768 | 1 a 393216 | Maximum tokens reserved for the reasoning process. Up to 393216. |
| reasoning_effort | enum | medium | none, low, medium, high, max | Reasoning effort level. none disables thinking. low, medium, high, and max set bounded thinking budgets sized to the selected model. Sent as an OpenAI-style... |
| response_format | enum | - | - | Constrain the output to JSON. Use JSON mode for any valid JSON object, or JSON schema to force output that matches a schema you provide. |
| web_search_linkup | boolean | false | - | Optional web search powered by Linkup. When enabled, recent web sources are retrieved using your latest user message as the query and provided to the model as additional context. Adds $0.013 per call when invoked on top of the model's normal token cost. Disabled by default. |
| disable_formatting | boolean | false | - | When enabled, the gateway will not append the "Sources" footer to assistant responses that used Linkup web search. Useful when the model output is piped to another... |
Thinking is enabled by default and can be disabled. Reasoning tokens are billed as output tokens. Optional Linkup web search is billed only when invoked.
En EmpirioLabs, DeepSeek V4 Pro 0813 se factura por uso: Input $1.32 per 1M prompt tokens; Output $3.96 per 1M generated tokens; Web Search (Linkup) $0.013 per call when invoked. La tabla de tarifas en vivo de esta página siempre coincide con lo que cobra la API.
DeepSeek V4 Pro 0813 admite una ventana de contexto de 1M tokens con hasta 393.216 tokens de salida por respuesta.
Sí. DeepSeek V4 Pro 0813 sirve la API de Chat Completions compatible con OpenAI, así que los SDKs de OpenAI existentes funcionan apuntando base_url a https://api.empiriolabs.ai/v1 y usando el id de modelo deepseek-v4-pro-0813.
Sí. El playground de EmpirioLabs ejecuta DeepSeek V4 Pro 0813 en el navegador con los mismos parámetros que expone la API, para que pruebes prompts antes de escribir código.
Crea una cuenta de EmpirioLabs y genera una clave en API Keys en el panel. La facturación es con créditos de pago por uso, así que solo pagas por las solicitudes que haces.
Consulta nuestros precios o contacta con nosotros si quieres que tu propio modelo se implemente en nuestra pila.
