DeepSeek-V3.2

Last reviewed: April 24, 2026

Status note: This page is a historical and technical guide to DeepSeek‑V3.2, the open-weight model released by DeepSeek in December 2025.
It is not a live tracker for the latest DeepSeek hosted API model names, API pricing, or current production endpoints. Hosted API aliases can change over time. For current API model names and pricing, always check the official DeepSeek API documentation.

DeepSeek‑V3.2 is an open-weight large language model released by DeepSeek on December 1, 2025. It was introduced as the official successor to DeepSeek‑V3.2‑Exp and positioned as a reasoning-first model built for long-context tasks, agent workflows, tool use, and complex problem solving.

This article explains what DeepSeek‑V3.2 was, what made it technically important, how its open weights can be understood, and how its historical API status changed after later DeepSeek platform updates. The goal is to preserve DeepSeek‑V3.2 as a stable reference page without implying that it is the newest or current hosted API model.

DeepSeek‑V3.2 at a Glance

Item	Details
Model name	DeepSeek‑V3.2
Release date	December 1, 2025
Release type	Open-weight model release
License	MIT License, according to the official Hugging Face model card
Model size	685B parameters, according to the official model card
Main focus	Reasoning, long-context processing, tool use, and agentic AI workflows
Historical API status	At launch, DeepSeek‑V3.2 was available on App, Web, and API
Current page purpose	Historical and technical guide, not a current API/pricing tracker

What Is DeepSeek‑V3.2?

DeepSeek‑V3.2 is a large open-weight language model designed to combine efficient long-context processing with strong reasoning and agentic capabilities. DeepSeek introduced it after DeepSeek‑V3.2‑Exp as a more mature model generation for reasoning-heavy tasks and tool-based workflows.

The model is especially notable for three technical themes:

• Efficient long-context attention: DeepSeek‑V3.2 introduced DeepSeek Sparse Attention, also known as DSA, to reduce the cost of processing long sequences.
• Reasoning-oriented post-training: DeepSeek described V3.2 as a reasoning-first model, with additional reinforcement-learning style training aimed at stronger reasoning and agent performance.
• Tool-use and agent workflows: The model was trained to handle complex interactive tasks, including tool-use scenarios and multi-step instructions.

Because DeepSeek‑V3.2 is an open-weight model, it remains relevant even after later hosted API model updates. Developers, researchers, and model evaluators can still study the architecture, model card, technical report, and released weights as part of the broader DeepSeek model history.

Important API Status Update

When DeepSeek‑V3.2 launched in December 2025, DeepSeek stated that it was live on App, Web, and API. At that time, the API aliases deepseek-chat and deepseek-reasoner were upgraded to DeepSeek‑V3.2’s non-thinking and thinking modes.

That historical mapping should not be treated as permanent. After DeepSeek’s later V4 Preview update on April 24, 2026, the hosted API moved to newer V4 model names. DeepSeek’s official documentation states that deepseek-chat and deepseek-reasoner became legacy compatibility aliases and no longer identify DeepSeek‑V3.2 in the hosted API.

For this reason, this page does not provide current hosted API code examples for DeepSeek‑V3.2. If you are building against DeepSeek’s cloud API, check the official DeepSeek API documentation for the latest model names, prices, context limits, and deprecation notices.

Why This Page Does Not Track Current API Pricing

DeepSeek API pricing and model availability can change over time. Because this page is intended to be a stable historical guide to DeepSeek‑V3.2, it avoids listing live API prices as if they were permanent.

If you are estimating production API cost, do not rely on old V3.2 pricing snippets copied from earlier articles. Use DeepSeek’s official pricing page instead, because hosted model names, cache-hit prices, cache-miss prices, output-token prices, and maximum output limits may change across model generations.

DeepSeek‑V3.2 Key Innovations

DeepSeek Sparse Attention

DeepSeek Sparse Attention, or DSA, is one of the main architectural ideas associated with DeepSeek‑V3.2. Instead of forcing every token to attend to every previous token in a fully dense way, DSA is designed to help the model focus computation on the most relevant parts of a long context.

This matters because long-context models can become expensive when attention costs grow with sequence length. Sparse attention techniques aim to reduce compute and memory pressure while preserving the model’s ability to reason over long inputs.

Mixture-of-Experts Scale

DeepSeek‑V3.2 belongs to DeepSeek’s large Mixture-of-Experts model family. The official Hugging Face model card lists the model size as 685B parameters. In a Mixture-of-Experts design, only a subset of the model’s experts are activated for each token, which allows a model to have very large total capacity while keeping per-token computation more manageable than activating all parameters at once.

Agentic Task Training

DeepSeek‑V3.2 was positioned as a model for agentic tasks, not just ordinary chat. DeepSeek described a large-scale agentic task synthesis pipeline involving many simulated environments and complex instructions. The purpose was to improve the model’s ability to follow multi-step goals, use tools, and generalize across interactive workflows.

DeepSeek‑V3.2 and Tool Use

One of the model’s notable features was its support for tool-use workflows. Tool use allows a model to request an external function or API call, such as a calculator, search function, database lookup, or internal business tool, instead of trying to answer everything from text generation alone.

In the DeepSeek‑V3.2 generation, this was especially important because DeepSeek emphasized “thinking in tool-use” and agent-style behavior. For developers and researchers, this made V3.2 relevant for studying how language models can combine reasoning, external tools, and structured outputs.

For live hosted API implementation details, however, developers should consult the current DeepSeek documentation. Tool-call schemas, supported model names, thinking-mode parameters, and compatibility behavior may change after later model updates.

DeepSeek‑V3.2‑Speciale

DeepSeek also introduced DeepSeek‑V3.2‑Speciale, a high-compute reasoning variant focused on maximum reasoning performance. DeepSeek described Speciale as stronger on difficult reasoning tasks but more expensive in token usage and less suitable for ordinary tool-based production workflows.

DeepSeek’s official December 2025 release note stated that DeepSeek‑V3.2‑Speciale was served through a temporary endpoint and that this access was available only until December 15, 2025, 15:59 UTC. Therefore, Speciale should be treated as a historical or research-focused variant unless DeepSeek later provides a new official access method.

The official Hugging Face model card also notes that DeepSeek‑V3.2‑Speciale was designed for deep reasoning tasks and does not support tool-calling functionality. This distinction matters for anyone comparing the standard V3.2 model with the Speciale variant.

Open Weights and Local Deployment

DeepSeek‑V3.2 remains important because its weights were released publicly. The official Hugging Face model card lists the repository license as MIT, which makes the model notable among large open-weight LLM releases.

Open weights do not mean the model is easy to run on consumer hardware. DeepSeek‑V3.2 is a very large model and requires serious infrastructure for local deployment or serious experimentation. Developers interested in local use should read the official model card, deployment notes, technical report, and community tooling before planning a production setup.

For many teams, the most practical value of the open release is not necessarily running the full model locally, but being able to inspect the model card, compare evaluations, study the technical report, and understand how V3.2 fits into DeepSeek’s model evolution.

Context Window and Long-Context Use

DeepSeek‑V3.2 was associated with long-context processing and efficient attention. Earlier V3.2 documentation and articles often discussed the model in relation to a 128K-token context window.

On this page, context length should be understood as part of the historical V3.2 model discussion, not as a statement about the latest DeepSeek hosted API. Hosted API context windows may change when DeepSeek upgrades model generations. For current hosted API limits, always use the official DeepSeek model and pricing page.

How to Use This Page Correctly

This page is useful if you want to understand DeepSeek‑V3.2 as a model release: what it introduced, why it mattered, how it compared with earlier DeepSeek models, and why it became part of the open-weight LLM ecosystem.

This page is not the right source for:

• the latest DeepSeek API model names;
• current DeepSeek API pricing;
• current deprecation dates;
• current production endpoint behavior;
• current maximum context or output limits for hosted models.

For those live platform details, use the official DeepSeek API documentation. Keeping this distinction clear helps avoid outdated claims and makes the page more durable over time.

DeepSeek‑V3.2 vs Later Hosted API Models

DeepSeek‑V3.2 should be understood as a specific historical model generation, not as a permanent API identity. Hosted API aliases such as deepseek-chat and deepseek-reasoner have changed meaning across DeepSeek releases.

This is why developers should avoid assuming that an old API alias always points to the same underlying model. A model page can remain accurate by describing what was true at the time of the release, while a live API guide must be updated whenever the platform changes.

DeepSeek‑V3.2 FAQ

Sources

• DeepSeek official DeepSeek‑V3.2 release note
• DeepSeek official API change log
• DeepSeek official models and pricing page
• DeepSeek official API quick start
• Official DeepSeek‑V3.2 Hugging Face model card
• Official DeepSeek‑V3.2‑Speciale Hugging Face model card