R1 Distill Qwen 1.5B

DeepSeek chatreasoningcode Free

API ID: deepseek/deepseek-r1-distill-qwen-1.5b

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

About R1 Distill Qwen 1.5B

DeepSeek R1 Distill Qwen 1.5B is a distilled large language model based on [Qwen 2.5 Math 1.5B](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B), using outputs from [DeepSeek R1](/deepseek/deepseek-r1). It's a very small and efficient model which outperforms [GPT 4o 0513](/openai/gpt-4o-2024-05-13) on Math Benchmarks. Other benchmark results include: - AIME 2024 pass@1: 28.9 - AIME 2024 cons@64: 52.7 - MATH-500 pass@1: 83.9 The model leverages fine-tuning from DeepSeek R1's outputs, enabling competitive performance comparable to larger frontier models.

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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
2025-01-31
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 1.5B 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 1.5B 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-1.5b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)