deepseek-v3-2
DeepSeek-V3.2 balances high computational efficiency with strong reasoning and agentic tool use. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism.
Pricing: Input 52 credits / 1M tokens (≈ $0.26), Output 76 credits / 1M tokens (≈ $0.38).
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DeepSeek V3.2 API on ModelFold
DeepSeek-V3.2 balances high computational efficiency with strong reasoning and agentic tool use. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism. Try DeepSeek V3.2 in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the DeepSeek V3.2 API
DeepSeek V3.2 at a glance
DeepSeek V3.2 is a chat model from DeepSeek. It accepts text as input and returns text, with a context window of up to 164K tokens.
Use it without hosting anything
On ModelFold you call DeepSeek V3.2 with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of DeepSeek V3.2
Up to 164K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Function calling
DeepSeek V3.2 supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Reasoning mode
DeepSeek V3.2 can produce reasoning before its final answer; in the Playground you can switch reasoning on or off to compare results.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use DeepSeek V3.2 on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how DeepSeek V3.2 responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "deepseek-v3-2" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with DeepSeek V3.2
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
Tool-calling backends
Route requests, call functions and chain API calls as the worker model inside larger agent systems.
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Frequently Asked Questions
What is DeepSeek V3.2?⌄
DeepSeek-V3.2 balances high computational efficiency with strong reasoning and agentic tool use. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism.
Which inputs does DeepSeek V3.2 support?⌄
DeepSeek V3.2 accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of DeepSeek V3.2?⌄
Up to 164K tokens, shared between your input and the model’s output.
Does DeepSeek V3.2 support function calling?⌄
Yes. DeepSeek V3.2 supports tools / function calling through the standard tools parameter of the chat completions API.
How is DeepSeek V3.2 billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call DeepSeek V3.2 through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "deepseek-v3-2", using your ModelFold API key as the Bearer token.
| Input | 52 credits 1M tokens≈ $0.26 |
| Output | 76 credits 1M tokens≈ $0.38 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"deepseek-v3-2","messages":[{"role":"user","content":"Hello"}]}'