DeepSeek-V3.2 & V3.2-Speciale: A Complete Beginner’s Guide (With API Tutorial)

DeepSeek just surprised the entire AI community again—by releasing two new models at once:
✔ DeepSeek-V3.2
✔ DeepSeek-V3.2-Speciale

Both models are now available on the official web interface, mobile app, and API.
DeepSeek-V3.2 is already the default production model, while the Speciale variant is currently available only via a temporary API endpoint for community testing.

This guide walks you through:

• What’s new in both models
• How to use them on the web
• How to call the API
• Where to download the models
• Key FAQs for beginners

1. What’s New in DeepSeek-V3.2?

DeepSeek-V3.2 is designed to balance reasoning power with shorter output length, making it highly suitable for:

• Everyday Q&A
• General AI agent tasks
• Coding and debugging
• Scenarios requiring fast reasoning with minimal verbosity

Key Highlights

• GPT-5–level reasoning performance on public benchmarks
• Slightly below Gemini 3.0 Pro, but extremely competitive
• Much shorter output than Kimi-K2-Thinking → lower cost + faster inference
• Optimized for production and high-frequency use cases

DeepSeek-V3.2 is now the recommended model for general use.

2. What’s New in DeepSeek-V3.2-Speciale?

DeepSeek-V3.2-Speciale is the reasoning-enhanced edition of V3.2.

It combines:

• DeepSeek-V3.2 architecture
• DeepSeek-Math-V2’s theorem-proving and logic capabilities

What It’s Designed For

• Long-chain reasoning
• Formal mathematical proofs
• Multi-step logic tasks
• Complex instruction following

Performance

On mainstream reasoning benchmarks, Speciale performs on par with Gemini-3.0-Pro.

Note: The model is API-only for now and meant for research and evaluation.

3. Try DeepSeek-V3.2 on the Web

This is the easiest way to start using the new model:

👉 https://chat.deepseek.com

Steps:

1. Visit the site
2. Log in
3. Select DeepSeek-V3.2
4. Start chatting

No additional setup needed.

4. Using DeepSeek API (Python & cURL Examples)

DeepSeek uses OpenAI-compatible API endpoints.

4.1 Python Example

import requests

url = "https://api.deepseek.com/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_API_KEY"
}

data = {
    "model": "deepseek-v3.2",
    "messages": [
        {"role": "user", "content": "Explain quantum mechanics in simple terms."}
    ]
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

4.2 Using DeepSeek-V3.2-Speciale

Just switch the model name:

"model": "deepseek-v3.2-speciale"

4.3 cURL Example

curl https://api.deepseek.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
        "model": "deepseek-v3.2",
        "messages": [{"role": "user", "content": "Write a short poem about winter."}]
      }'

5. Download the Models (HuggingFace & ModelScope)

DeepSeek-V3.2

• HuggingFace: https://huggingface.co/deepseek-ai/DeepSeek-V3.2

• ModelScope: https://modelscope.cn/models/deepseek-ai/DeepSeek-V3.2

DeepSeek-V3.2-Speciale

• HuggingFace: https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Speciale

• ModelScope: https://modelscope.cn/models/deepseek-ai/DeepSeek-V3.2-Speciale

These models can be loaded using Transformers, VLLM, Ollama, or LM Studio depending on your hardware.

6. Choosing Between V3.2 and Speciale

Task Type	Recommended Model
General Q&A	V3.2
Fast, low-cost usage	V3.2
Coding & debugging	V3.2
Deep reasoning	Speciale
Formal math proofs	Speciale
Multi-step logic	Speciale

If unsure, start with V3.2, then switch to Speciale for more complex reasoning tasks.

FAQ

1. Is DeepSeek-V3.2 free to use?

You can test it for free on the official web platform. API usage requires credits depending on your plan.

2. Why is the Speciale model not shown on the website UI?

Speciale is currently offered only as an experimental API model, allowing the community to benchmark and evaluate it.

3. How does V3.2 differ from previous versions?

V3.2 improves reasoning, reduces unnecessary output length, and significantly decreases overall latency and computation cost.

4. Can these models be run locally?

Yes. Both models are available on HuggingFace and ModelScope, but they require powerful GPUs due to their large size.

5. When will DeepSeek release V4 or R2 models?

There is no official date yet. However, many users expect major releases around the Lunar New Year period.