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Drun Deepseek V3.2
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Drun Deepseek V3.2

drun-deepseek-v3.2
DeepSeek
The model DeepSeek-V3.2-Exp is officially named deepseek-chat on the website. It is an experimental version. As an intermediate step towards the next-generation architecture, V3.2-Exp introduces DeepSeek Sparse Attention (a sparse attention mechanism) based on V3.1-Terminus, exploring and validating

Pricing

  • Input Tokens: $0.274 /M tokens
  • Output Tokens: $0.411 /M tokens
  • Cache Read: $0.0274 /M tokens

Input Modalities

  • Text

Output Modalities

  • Text

Capabilities

  • Tools
  • Tool calling
  • Structured outputs

Try this model

Python
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["AIHUBMIX_API_KEY"],
    base_url="https://shkq.org/v1",
)

response = client.chat.completions.create(
    model="drun-deepseek-v3.2",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

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

Frequently asked questions

What is Drun Deepseek V3.2?

The model DeepSeek-V3.2-Exp is officially named deepseek-chat on the website. It is an experimental version. As an intermediate step towards the next-generation architecture, V3.2-Exp introduces DeepSeek Sparse Attention (a sparse attention mechanism) based on V3.1-Terminus, exploring and validating

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