DeepSeek R1 32B

DeepSeek R1 32B is a state-of-the-art reasoning model from the DeepSeek series, specifically designed to excel at complex problem-solving and advanced reasoning tasks. It significantly outperforms conventional instruction-tuned models, particularly on hard problems that require thoughtful analysis.

Key Features

• Parameters: 32 billion
• Architecture: Transformers with RoPE and FlashAttention-2
• Context Length: Up to 131,072 tokens.
• Key Capability: Enhanced reasoning through sophisticated step-by-step thinking
• Performance: Competitive with other large reasoning models at similar parameter scales

API Reference

Endpoint

Our API follows the OpenAI-compatible format:

POST /v1/chat/completions

Model Name

Use the following model identifier in your requests:

deepseek-r1-32b

Parameters

• model (string): The model identifier (“deepseek-r1-32b”).
• messages (array): An array of message objects that represent the conversation history, each with:
  • role (string): Either “system”, “user”, or “assistant”.
  • content (string): The content of the message.
• max_tokens (int): Max output tokens (default: 100, max: 32768).
• temperature (float): Sampling temperature (recommended: 0.6).
• top_p (float): Nucleus sampling parameter (recommended: 0.95).
• top_k (int): Top-k sampling parameter (recommended: 20-40).
• stream (boolean): Whether to stream the response (default: false).

Optimal Usage

For best results:

• Enable the model’s thinking process with the <think> tag in system prompts
• Use temperature=0.6 and top_p=0.95 instead of greedy decoding
• For math problems, include “Please reason step by step” in your prompt

Code Examples

Choose your preferred programming language:

Python

Standard Request

from openai import OpenAI
client = OpenAI(
    api_key="your-deeprequest-key",
    base_url="https://api.deeprequest.io/v1"
)

# Standard request
response = client.chat.completions.create(
    model="deepseek-r1-32b",
    messages=[
        {"role": "system", "content": "You are a helpful assistant that thinks step by step."},
        {"role": "user", "content": "How many r's are in the word 'strawberry'?"}
    ],
    temperature=0.6,
    max_tokens=500
)

# Print the response
print(response.choices[0].message.content)

Streaming Request

from openai import OpenAI
client = OpenAI(
    api_key="your-deeprequest-key",
    base_url="https://api.deeprequest.io/v1"
)

# Streaming response
stream = client.chat.completions.create(
    model="deepseek-r1-32b",
    messages=[
        {"role": "system", "content": "You are a helpful assistant that thinks step by step."},
        {"role": "user", "content": "How many r's are in the word 'strawberry'?"}
    ],
    temperature=0.6,
    max_tokens=500,
    stream=True  # Enable streaming
)

# Process the streaming response
print("Streaming response:")
for chunk in stream:
    if chunk.choices[0].delta.content is not None:
        print(chunk.choices[0].delta.content, end="", flush=True)

Node.js

Standard Request

// Install: npm install openai
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'your-deeprequest-key',
  baseURL: 'https://api.deeprequest.io/v1'
});

// Standard request
async function chatWithAI() {
  const response = await client.chat.completions.create({
    model: 'deepseek-r1-32b',
    messages: [
      { role: 'system', content: 'You are a helpful assistant that thinks step by step.' },
      { role: 'user', content: 'How many r\'s are in the word \'strawberry\'?' }
    ],
    temperature: 0.6,
    max_tokens: 500
  });

  // Print the response
  console.log(response.choices[0].message.content);
}

chatWithAI();

Streaming Request

// Install: npm install openai
import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'your-deeprequest-key',
  baseURL: 'https://api.deeprequest.io/v1'
});

// Streaming response
async function streamChatWithAI() {
  const stream = await client.chat.completions.create({
    model: 'deepseek-r1-32b',
    messages: [
      { role: 'system', content: 'You are a helpful assistant that thinks step by step.' },
      { role: 'user', content: 'How many r\'s are in the word \'strawberry\'?' }
    ],
    temperature: 0.6,
    max_tokens: 500,
    stream: true  // Enable streaming
  });

  // Process the streaming response
  console.log("Streaming response:");
  let responseText = '';
  for await (const chunk of stream) {
    if (chunk.choices[0]?.delta?.content) {
      const content = chunk.choices[0].delta.content;
      process.stdout.write(content);
      responseText += content;
    }
  }

  return responseText;
}

streamChatWithAI();

Go

Standard Request

package main

import (
  "context"
  "fmt"
  "github.com/sashabaranov/go-openai"
)

func main() {
  // Initialize client with DeepRequest configuration
  config := openai.DefaultConfig("your-deeprequest-key")
  config.BaseURL = "https://api.deeprequest.io/v1"
  client := openai.NewClientWithConfig(config)

  // Standard request
  resp, err := client.CreateChatCompletion(
    context.Background(),
    openai.ChatCompletionRequest{
      Model: "deepseek-r1-32b",
      Messages: []openai.ChatCompletionMessage{
        {
          Role:    openai.ChatMessageRoleSystem,
          Content: "You are a helpful assistant that thinks step by step.",
        },
        {
          Role:    openai.ChatMessageRoleUser,
          Content: "How many r's are in the word 'strawberry'?",
        },
      },
      Temperature: 0.6,
      MaxTokens:   500,
    },
  )

  if err != nil {
    fmt.Printf("Error: %v\n", err)
    return
  }

  // Print the response
  fmt.Println(resp.Choices[0].Message.Content)
}

Streaming Request

package main

import (
  "context"
  "fmt"
  "github.com/sashabaranov/go-openai"
  "io"
)

func main() {
  // Initialize client with DeepRequest configuration
  config := openai.DefaultConfig("your-deeprequest-key")
  config.BaseURL = "https://api.deeprequest.io/v1"
  client := openai.NewClientWithConfig(config)

  // Streaming response
  fmt.Println("Streaming response:")
  stream, err := client.CreateChatCompletionStream(
    context.Background(),
    openai.ChatCompletionRequest{
      Model: "deepseek-r1-32b",
      Messages: []openai.ChatCompletionMessage{
        {
          Role:    openai.ChatMessageRoleSystem,
          Content: "You are a helpful assistant that thinks step by step.",
        },
        {
          Role:    openai.ChatMessageRoleUser,
          Content: "How many r's are in the word 'strawberry'?",
        },
      },
      Temperature: 0.6,
      MaxTokens:   500,
      Stream:      true,  // Enable streaming
    },
  )
  if err != nil {
    fmt.Printf("Stream error: %v\n", err)
    return
  }
  defer stream.Close()

  // Process the streaming response
  var fullResponse string
  for {
    response, err := stream.Recv()
    if err == io.EOF {
      break
    }
    if err != nil {
      fmt.Printf("Stream error: %v\n", err)
      return
    }
    content := response.Choices[0].Delta.Content
    fmt.Print(content)
    fullResponse += content
  }

  fmt.Println("\nFull response received!")
}

Ruby

Standard Request

# Install: gem install ruby-openai
require 'openai'

# Initialize client with DeepRequest configuration
client = OpenAI::Client.new(
  access_token: 'your-deeprequest-key',
  uri_base: 'https://api.deeprequest.io/v1'
)

# Standard request
response = client.chat(
  parameters: {
    model: 'deepseek-r1-32b',
    messages: [
      { role: 'system', content: 'You are a helpful assistant that thinks step by step.' },
      { role: 'user', content: 'How many r\'s are in the word \'strawberry\'?' }
    ],
    temperature: 0.6,
    max_tokens: 500
  }
)

# Print the response
puts response.dig('choices', 0, 'message', 'content')

Streaming Request

# Install: gem install ruby-openai
require 'openai'

# Initialize client with DeepRequest configuration
client = OpenAI::Client.new(
  access_token: 'your-deeprequest-key',
  uri_base: 'https://api.deeprequest.io/v1'
)

# Streaming response
stream_response = client.chat(
  parameters: {
    model: 'deepseek-r1-32b',
    messages: [
      { role: 'system', content: 'You are a helpful assistant that thinks step by step.' },
      { role: 'user', content: 'How many r\'s are in the word \'strawberry\'?' }
    ],
    temperature: 0.6,
    max_tokens: 500,
    stream: true  # Enable streaming
  }
)

# Process the streaming response
puts "Streaming response:"
response_content = ""

stream_response.each do |chunk|
  content = chunk.dig('choices', 0, 'delta', 'content')
  if content
    print content
    response_content += content
  end
end

puts "\nFull response: #{response_content}"

PHP

Standard Request

<?php
// Install: composer require openai-php/client
require 'vendor/autoload.php';

// Initialize client with DeepRequest configuration
$client = OpenAI::client('your-deeprequest-key', [
    'base_uri' => 'https://api.deeprequest.io/v1'
]);

// Standard request
$response = $client->chat()->create([
    'model' => 'deepseek-r1-32b',
    'messages' => [
        ['role' => 'system', 'content' => 'You are a helpful assistant that thinks step by step.'],
        ['role' => 'user', 'content' => 'How many r\'s are in the word \'strawberry\'?']
    ],
    'temperature' => 0.6,
    'max_tokens' => 500
]);

// Print the response
echo $response->choices[0]->message->content;
?>

Streaming Request

<?php
// Install: composer require openai-php/client
require 'vendor/autoload.php';

// Initialize client with DeepRequest configuration
$client = OpenAI::client('your-deeprequest-key', [
    'base_uri' => 'https://api.deeprequest.io/v1'
]);

// Streaming response
$stream = $client->chat()->createStreamed([
    'model' => 'deepseek-r1-32b',
    'messages' => [
        ['role' => 'system', 'content' => 'You are a helpful assistant that thinks step by step.'],
        ['role' => 'user', 'content' => 'How many r\'s are in the word \'strawberry\'?']
    ],
    'temperature' => 0.6,
    'max_tokens' => 500,
    'stream' => true  // Enable streaming
]);

// Process the streaming response
echo "Streaming response:\n";
$responseContent = '';

foreach ($stream as $response) {
    if ($content = $response->choices[0]->delta->content) {
        echo $content;
        flush();
        $responseContent .= $content;
    }
}

echo "\nFull response: " . $responseContent;
?>

cURL

Standard Request

curl -X POST https://api.deeprequest.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek-r1-32b",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant that thinks step by step."
      },
      {
        "role": "user",
            "content": "How many r'\''s are in the word '\''strawberry'\''?"
      }
    ],
    "max_tokens": 500,
    "temperature": 0.6,
    "stream": false
  }'

Streaming Request

curl -X POST https://api.deeprequest.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek-r1-32b",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant that thinks step by step."
      },
      {
        "role": "user",
        "content": "How many r'\''s are in the word '\''strawberry'\''?"
      }
    ],
    "max_tokens": 500,
    "temperature": 0.6,
    "stream": true
  }'

Response Format

Here’s an example response from the model:

{
  "id": "chatcmpl-123456789",
  "object": "chat.completion",
  "created": 1704476253,
  "model": "deepseek-r1-32b",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "<think>\nLet me analyze the word 'strawberry' letter by letter.\nS-t-r-a-w-b-e-r-r-y\n\nI can see that the letter 'r' appears 3 times in the word 'strawberry':\n1. The third letter: str\n2. The eighth letter: strawber\n3. The ninth letter: strawberr\n\nSo there are 3 r's in the word 'strawberry'.\n</think>\n\nTo count the number of r's in 'strawberry', I'll examine each letter:\n\ns-t-r-a-w-b-e-r-r-y\n\nI can see the letter 'r' appears three times in the word:\n- First 'r': 3rd position\n- Second 'r': 8th position \n- Third 'r': 9th position\n\nTherefore, there are 3 r's in the word 'strawberry'."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 24,
    "completion_tokens": 215,
    "total_tokens": 239
  }
}

Additional Resources

For detailed API documentation, please visit our API Docs or ReDoc.

Pricing details at Pricing.