Pares DeepSeek R1 chain-of-thought razonando con la generación antropópica de Claude creativa y código detrás de una interfaz unificada y controlada por datos.
WinFuncGeneracion de textoLanzado Jan 26, 2025Inferencia nativaPares DeepSeek R1 chain-of-thought razonando con la generación antropópica de Claude creativa y código detrás de una interfaz unificada y controlada por datos.
También conocido como WinFunc DeepReasoning
deepreasoningPOST /v1/chat/completionsPOST /v1/responsesPOST /v1/messagesLive pay-as-you-go rates from the EmpirioLabs catalog. You are billed only for what you use, with no monthly minimum.
DeepReasoning serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id deepreasoning. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepreasoning",
"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="deepreasoning",
messages=[{"role": "user", "content": "Write a haiku about the ocean."}],
)
print(response.choices[0].message.content)Request parameters supported by the DeepReasoning API on EmpirioLabs. Defaults apply when a field is omitted.
| Parámetro | Tipo | Predeterminado | Rango / valores | Descripción |
|---|---|---|---|---|
| temperature | number | 0.7 | 0 to 2 | Sampling temperature. Applies to both the R1 reasoning stage and the Claude synthesis stage. |
| top_p | number | 0.9 | 0 to 1 | Nucleus sampling. Applies to both the R1 reasoning stage and the Claude synthesis stage. |
| max_tokens | number | 8192 | 1 to 65536 | Maximum output tokens for the Claude synthesis stage. |
| anthropic_model | enum | claude-sonnet-4-5-20250929 | claude-sonnet-4-5-20250929, claude-haiku-4-5-20251001, claude... | Choose the Claude model to pair with DeepSeek R1 0528 reasoning. The R1 model produces the chain-of-thought; the Claude model synthesizes the final answer. |
| 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... |
| 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... |
Razón R1-0528 emparejado con uno de: Claude Sonnet 4.5 (por defecto), Haiku 4.5, Opus 4.5, Sonnet 4, Opus 4.1, Opus 4, Sonnet 3.7, Haiku 3.5, Opus 3. Sobre "Inferencia nativa" para este modelo EmpirioLabs acoge la lógica de código abierto del proyecto API/orchestration desde su repo GitHub en nuestra propia infraestructura , esa es la parte "nativa". Los modelos subyacentes (R1-0528 razonamiento + el modelo de terminación Claude que elija) todavía están marcados a través de sus respectivas API oficiales. No albergamos los pesos del modelo.
On EmpirioLabs, DeepReasoning is billed pay as you go: R1-0528 + Claude Sonnet 4.5 (Default) In $0.012 / Out $0.058 por tokens 1K; R1-0528 + Claude Haiku 4.5 In $0.0048 / Out $0.023 por tokens 1K; R1-0528 + Claude Opus 4.5 In $0.019 / Out $0.092 por tokens 1K. The live rate card on this page always matches what the API charges.
Yes. DeepReasoning serves the OpenAI-compatible Chat Completions API, so existing OpenAI SDKs work by pointing base_url at https://api.empiriolabs.ai/v1 and setting the model id to deepreasoning.
Yes. The EmpirioLabs playground runs DeepReasoning in the browser with the same parameters the API exposes, so you can test prompts before writing code.
Create an EmpirioLabs account, then generate a key under API Keys in the dashboard. Billing is pay-as-you-go credits, so you only pay for the requests you make.
Check out our pricing or reach out if you want your own model deployed on our stack.
