deepseek-v3-2-exp
DeepSeek-V3.2-Exp is an experimental model released as an intermediate step between V3.1 and later architectures. It introduces DeepSeek Sparse Attention (DSA) for more efficient long-context processing.
Pricing: Input 54 credits / 1M tokens (≈ $0.27), Output 82 credits / 1M tokens (≈ $0.41).
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DeepSeek V3.2 Exp API on ModelFold
DeepSeek-V3.2-Exp is an experimental model released as an intermediate step between V3.1 and later architectures. It introduces DeepSeek Sparse Attention (DSA) for more efficient long-context processing. Try DeepSeek V3.2 Exp in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the DeepSeek V3.2 Exp API
DeepSeek V3.2 Exp at a glance
DeepSeek V3.2 Exp 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 Exp 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 Exp
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 Exp 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 Exp 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 Exp 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 Exp 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-exp" 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 Exp
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
Long-document workflows
Feed in long reports, contracts, manuals or codebases and ask for summaries, comparisons and answers grounded in the material.
AI coding assistants
Generate, explain, debug and refactor code, review pull requests and work through multi-file changes in developer tools and IDE plugins.
Frequently Asked Questions
What is DeepSeek V3.2 Exp?⌄
DeepSeek-V3.2-Exp is an experimental model released as an intermediate step between V3.1 and later architectures. It introduces DeepSeek Sparse Attention (DSA) for more efficient long-context processing.
Which inputs does DeepSeek V3.2 Exp support?⌄
DeepSeek V3.2 Exp 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 Exp?⌄
Up to 164K tokens, shared between your input and the model’s output.
Does DeepSeek V3.2 Exp support function calling?⌄
Yes. DeepSeek V3.2 Exp supports tools / function calling through the standard tools parameter of the chat completions API.
How is DeepSeek V3.2 Exp 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 Exp through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "deepseek-v3-2-exp", using your ModelFold API key as the Bearer token.
| Input | 54 credits 1M tokens≈ $0.27 |
| Output | 82 credits 1M tokens≈ $0.41 |
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-exp","messages":[{"role":"user","content":"Hello"}]}'