DeepSeek R1 (Reasoner)

DeepSeek R1 uses chain-of-thought reasoning to solve complex problems. Excels at mathematics, formal logic, scientific analysis, and multi-step reasoning tasks.

Use Cases

Quick Start

curl https://aiwave.live/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{"model":"deepseek-reasoner","messages":[{"role":"user","content":"Hello!"}]}'

What it costs in practice

These figures come straight from the live rate above — monthly token volume multiplied by the per-million price. Adjust the volumes to match your own traffic.

Workload	Assumption	Monthly tokens	Monthly cost
Chatbot	~50k short conversations	5.0M in / 1.5M out	$8.70
Coding assistant	one developer, full-time	20.0M in / 4.0M out	$30.45
RAG / document Q&A	long retrieved contexts	50.0M in / 2.0M out	$58.72

Rates are pulled from the live pricing endpoint. Token accounting is returned in the usage field of every non-streaming response.

Quick start

The endpoint is OpenAI-compatible, so the official SDKs work once you change base_url. Nothing else in your code needs to move.

from openai import OpenAI

client = OpenAI(
    api_key="sk-YOUR_KEY",
    base_url="https://aiwave.live/v1",
)

response = client.chat.completions.create(
    model="deepseek-reasoner",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)
print(response.usage)   # exact token counts for cost tracking

Streaming uses the same server-sent-event format as OpenAI:

stream = client.chat.completions.create(
    model="deepseek-reasoner",
    messages=[{"role": "user", "content": "Explain vector search"}],
    stream=True,
)
for chunk in stream:
    delta = chunk.choices[0].delta.content
    if delta:
        print(delta, end="", flush=True)

Node.js, LangChain, LlamaIndex, the Vercel AI SDK, Cursor and Cline all accept a custom base URL, so they work with this model without a dedicated provider plugin. Full parameter reference lives in the Chat Completions docs.

How it compares to sibling models

Same provider, same API surface — the practical difference is price and capability. Because every model here speaks the OpenAI wire format, switching between them is a one-word change to the model field.

Model ID	Input / 1M	Output / 1M
deepseek-r1-distill-qwen-14b	$0.0154	$0.0308
deepseek-r1-distill-qwen-32b	$0.0154	$0.0308
deepseek-v3	$0.154	$0.308
deepseek-v3.2-think	$0.154	$0.308
deepseek-chat	$0.182	$0.364
deepseek-v4-flash	$0.206	$0.412

Where to go next

• API documentation — auth, endpoints, error codes
• Live pricing for every model
• Model directory — compare context windows and capabilities
• Access Chinese AI models without a Chinese phone number
• Migrate an OpenAI app in two lines

Related Models