Name: DeepSeek V3.2 Exp API
Brand: DeepSeek

Overview

What is DeepSeek V3.2 Exp API?

DeepSeek-V3.2-Exp is an experimental variant of DeepSeek-V3.2 with extended context and non-thinking mode for fast responses.

Technical Specifications
- Supported inputs: Text
- Output: Text
- Context window: 128,000 tokens / Max output: 64,000 tokens
- Endpoint: /chat/completions

Performance Benchmarks
[embed]

DeepSeek V3.2 Exp API Pricing
- Input: $0.26 / 1M tokens
- Output: $0.52 / 1M tokens

Where to Use DeepSeek V3.2 Exp

Coding and code review
Generate, debug, and review code across languages, reading whole files or repos in a single prompt.

Agentic and multi-step workflows
Reliable tool-calling and instruction-following suit agent loops that plan, call tools, and iterate.

Long-document analysis
Summarize and extract from contracts, papers, and reports without aggressive chunking.

Code Sample
[embed]

Uptime and performance

Uptime (24h): 100%
Uptime (7d): 100%
Availability (24h): 93.0%
Error rate (24h): 7.0%
End-to-end latency (24h median): 38.9s
Time to first token (24h median): 2.1s
Throughput (24h median): 5.5 tok/s

Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.

Use cases

Long-context training and inference efficiency is a documented fit for DeepSeek V3.2 Exp, because it introduces DeepSeek Sparse Attention to improve efficiency in long-context scenarios. It is also suited to tool-use workflows, including thinking and non-thinking modes with tool calling.

It is documented for agentic workflows, including research assistants and search agents, with support for structured tool calling. It is also suited to coding and software engineering tasks, including code agents and debugging across large codebases or multi-file projects.

How to use DeepSeek V3.2 Exp API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to deepseek/deepseek-thinking-v3.2-exp.

import requests

r = requests.post(
    "https://api.aimlapi.com/v1/chat/completions",
    headers={"Authorization": "Bearer " + AIMLAPI_KEY},
    json={
      "model": "deepseek/deepseek-thinking-v3.2-exp",
      "messages": [
        {
          "role": "user",
          "content": "Hello!"
        }
      ]
    },
)
print(r.json())

const r = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "deepseek/deepseek-thinking-v3.2-exp",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }),
});
console.log(await r.json());

curl -X POST https://api.aimlapi.com/v1/chat/completions \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"deepseek/deepseek-thinking-v3.2-exp","messages":[{"role":"user","content":"Hello!"}]}'

OpenAI-compatible — swap the base URL and it works with your existing SDK.