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DeepSeek R1 Distill Qwen 32B
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DeepSeek R1 Distill Qwen 32B

DeepSeek-R1-Distill-Qwen-32B
DeepSeek
The model provider is the Sophnet platform. Deepseek-R1-Distill-Qwen-32B is a knowledge-distilled large language model based on Qwen 2.5 32B and trained using outputs from DeepSeek R1. DeepSeek-R1 addresses issues such as infinite repetition, poor readability, and language mixing by introducing cold-start data before reinforcement learning. DeepSeek-R1’s performance in mathematics, programming, and reasoning tasks is comparable to OpenAI-o1. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models based on Llama and Qwen. DeepSeek-R1-Distill-Qwen-32B outperforms OpenAI-o1-mini on multiple benchmark tests, setting new state-of-the-art results for dense models.

Pricing

  • Input Tokens: $0.28 /M tokens
  • Output Tokens: $0.84 /M tokens

Input Modalities

    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="DeepSeek-R1-Distill-Qwen-32B",
    messages=[
      {
        "role": "user",
        "content": "Hello, how are you?"
      }
    ],
    max_tokens=1024,
    stream=False,
)

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

    Frequently asked questions

    What is DeepSeek R1 Distill Qwen 32B?

    The model provider is the Sophnet platform. Deepseek-R1-Distill-Qwen-32B is a knowledge-distilled large language model based on Qwen 2.5 32B and trained using outputs from DeepSeek R1. DeepSeek-R1 addresses issues such as infinite repetition, poor readability, and language mixing by introducing cold-start data before reinforcement learning. DeepSeek-R1’s performance in mathematics, programming, and reasoning tasks is comparable to OpenAI-o1. To support the research community, we have open-sourced DeepSeek-R1-Zero, DeepSeek-R1, and six dense models based on Llama and Qwen. DeepSeek-R1-Distill-Qwen-32B outperforms OpenAI-o1-mini on multiple benchmark tests, setting new state-of-the-art results for dense models.

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