deepseek/deepseek-r1
64,000 context · $0.70/M input tokens · $2.50/M output 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....
Kullandıkça öde
Ön ödeme yok, yalnızca kullandığınız kadar ödeyin
API'mizle entegre etmek için aşağıdaki kod örneklerini kullanın:
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)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!
| 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 |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.8 |
| Output | $2.7 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-r1
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 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!"}]
}'
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....
Input
$0.7 /M
Output
$2.5 /M
Context
64K
Max Output
16K
Tool Use
Supported
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