---
title: "DeepSeek-V3.2-Exp released, training inference efficiency improved, API prices synchronized down"
description: "Today, we officially released the DeepSeek-V3.2-Exp model, which is an experimental version. This version introduces a sparse attention mechanism based on V3.1-Terminus, optimizing the training and in"
type: "news"
locale: "en"
url: "https://longbridge.com/en/news/276049041.md"
published_at: "2026-02-16T10:12:38.000Z"
---

# DeepSeek-V3.2-Exp released, training inference efficiency improved, API prices synchronized down

> Today, we officially released the DeepSeek-V3.2-Exp model, which is an experimental version. This version introduces a sparse attention mechanism based on V3.1-Terminus, optimizing the training and inference efficiency for long texts. The official app, web version, and mini-program have been updated to DeepSeek-V3.2-Exp, and the API prices have been significantly reduced. We welcome users to experience it and provide feedback

Today, we officially released the DeepSeek-V3.2-Exp model, which is an experimental version. As an intermediate step towards a new generation architecture, V3.2-Exp introduces DeepSeek Sparse Attention (a sparse attention mechanism) based on V3.1-Terminus, exploring optimizations and validations for training and inference efficiency with long texts.

Currently, the official app, web version, and mini program have all been updated to DeepSeek-V3.2-Exp, and the API has significantly reduced its prices. We welcome users to experience the testing and provide us with feedback

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---

> **Disclaimer**: This article is for reference only and does not constitute any investment advice.