DeepSeek R1 | Open-Source Reasoning LLM API

Name: DeepSeek R1 API
Brand: deepseek
Price: 0.7 USD
Availability: InStock

Utilizzo API

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

from openai import OpenAI

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

response = client.chat.completions.create(
    model="deepseek/deepseek-r1",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Introduzione al modello

Deepseek deepseek-r1

DeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens

DeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.

Fully open-source model & technical report.

MIT licensed: Distill & commercialize freely!

Why It Looks Great

Large Language Model architecture for efficient processing
64000 context window for long document handling
Competitive pricing at $0.8/$2.7 per million tokens

Key Features

Context Window: 64000 tokens
Max Output: 16000 tokens
Vision: Supported
Function Calling: Supported

Specifications

Specification	Value
Provider	Deepseek
Model Type	Large Language Model (LLM)
Architecture	N/A
Context Window	64000 tokens
Max Output	16000 tokens
Input	Text
Output	Text
Vision	Supported
Function Calling	Supported

Pricing

Token Type	Cost per Million Tokens
Input	$0.8
Output	$2.7

How to Use

Write your prompt — describe the task, provide context, and specify 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: deepseek/deepseek-r1

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="deepseek/deepseek-r1",
    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": "deepseek/deepseek-r1",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: deepseek/deepseek-r1
Provider: Deepseek

Domande frequenti su DeepSeek R1

Quanto costa DeepSeek R1 via API?+

Prezzi su WaveSpeedAI: $0.70 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 DeepSeek R1?+

DeepSeek R1 supporta fino a 64K token di contesto e fino a 16K token di output per richiesta.

DeepSeek R1 è compatibile con OpenAI?+

Sì. WaveSpeedAI espone DeepSeek R1 tramite un endpoint compatibile con OpenAI all'indirizzo https://llm.wavespeed.ai/v1. Punta l'SDK ufficiale di OpenAI a questa base URL con la tua API key WaveSpeedAI — senza altre modifiche al codice.

Come si inizia con DeepSeek R1?+

Accedi a WaveSpeedAI, crea una API key in Access Keys, poi invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. I nuovi account ricevono crediti gratuiti per testare DeepSeek R1.

Prezzi