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....
Pay-per-use
No upfront costs, pay only for what you use
Use the following code examples to integrate with our 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)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/deepseek-r1
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
Access DeepSeek R1 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Open PlaygroundPricing on WaveSpeedAI: $0.70 per million input tokens and $2.50 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
DeepSeek R1 supports up to 64K tokens of context with up to 16K tokens of output per request.
Yes. WaveSpeedAI exposes DeepSeek R1 through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate DeepSeek R1 before paying per token.