R1 Distill Qwen 7B

DeepSeek chatreasoningcode Free

API ID: deepseek/deepseek-r1-distill-qwen-7b

Input Price
Free
/1M tokens
Output Price
Free
/1M tokens

About R1 Distill Qwen 7B

DeepSeek-R1-Distill-Qwen-7B is a 7 billion parameter dense language model distilled from DeepSeek-R1, leveraging reinforcement learning-enhanced reasoning data generated by DeepSeek's larger models. The distillation process transfers advanced reasoning, math, and code capabilities into a smaller, more efficient model architecture based on Qwen2.5-Math-7B. This model demonstrates strong performance across mathematical benchmarks (92.8% pass@1 on MATH-500), coding tasks (Codeforces rating 1189), and general reasoning (49.1% pass@1 on GPQA Diamond), achieving competitive accuracy relative to larger models while maintaining smaller inference costs.

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Price Ranking
#6 lowest price among 1240 Chat models โ€” Top 20% cheapest!

Model Specifications

Context Length
131k
Max Output
โ€”
Release Date
2025-05-30
Capabilities
chat reasoning code
Input Modalities
text
Output Modalities
text

Best For

  • Complex reasoning, math problems, multi-step logic
  • Code generation, debugging, code review, refactoring
  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)
  • Simple Q&A (cheaper models available)
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This model is completely free!

No token costs - use it without worrying about API bills.

Estimate Token Usage

DeepSeek Model Lineup

Compare all models from DeepSeek to find the best fit

Model Input Output Context Capabilities
R1 Distill Qwen 7B Current Free Free 131k chat reasoning code
DeepSeek V3.1 Base Free Free 164k chat
DeepSeek V3.1 Base Free Free 164k chat
DeepSeek Prover V2 Free Free 164k chat
DeepSeek V3 Base Free Free 131k chat
DeepSeek V3 Base Free Free 131k chat

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๐Ÿš€ Quick Start

Get started with R1 Distill Qwen 7B API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-r1-distill-qwen-7b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)