Question 1

What is DeepSeek V3.2?

Accepted Answer

DeepSeek V3.2 is a 670B-parameter open-source large language model (LLM) that offers long-context reasoning, reliable tool use, and benchmark-level performance. It competes with top proprietary models like GPT-5 and Gemini while remaining free to use under the MIT license.

Question 2

How does DeepSeek V3.2 handle 128k token inputs efficiently?

Accepted Answer

DeepSeek V3.2 uses DeepSeek Sparse Attention (DSA), a two-stage mechanism where a compact indexer scans the full input and dense attention is applied to the top 2,048 relevant tokens. This enables linear scaling for long inputs without compromising accuracy.

Question 3

Is DeepSeek V3.2 really free to use?

Accepted Answer

Yes. DeepSeek V3.2 is released under the MIT license, allowing full commercial use, fine-tuning, and deployment without licensing fees.

Question 4

How can I try or deploy DeepSeek V3.2?

Accepted Answer

You can use the official API or demo to test DeepSeek V3.2 quickly. For full control, download the model weights and run it locally or in the cloud, ensuring your infrastructure matches the model's size.

Question 5

When should I use V3.2-Thinking vs. Speciale?

Accepted Answer

Use V3.2-Thinking for general-purpose, tool-integrated workflows. Choose Speciale for research, coding, or competition-grade reasoning where tool use isn't required.

DeepSeek V3.2: Performance, Benchmarks, and Tradeoffs

DeepSeek V3.2: Performance, Benchmarks, and Tradeoffs

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