Vivgrid: DeepSeek-V3.2
DeepSeek-V3.2 is a reasoning model from Vivgrid released on Dec 1, 2025. It reads text and writes text, with a 128K token context window and up to 128K tokens per reply.
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It costs $0.28 per million input tokens and $0.42 per million output tokens.
It supports tool calling, and its weights are open, so you can host it yourself.
- Modalities
- In / out price
- $0.28 / $0.42 per 1M
- Context
- 128K
- Max output
- 128K
- Released
- Dec 1, 2025
- Knowledge cutoff
- Jul 2024
- Tool calling
- Structured output
- Reasoning
- Prompt caching
- Open weights
- Free to use
DeepSeek-V3.2 pricing
USD, as listed on Oct 15, 2026. Most bills are input heavy, so the cached input rate matters as much as the headline price.
| Input | $0.28 / 1M tokens | |
|---|---|---|
| Output | $0.42 / 1M tokens |
What DeepSeek-V3.2 costs per month
Pick a workload close to yours or type your own volumes.
Supported request parameters
What you can set when you call DeepSeek-V3.2 through an OpenAI compatible API.
- Tools
tools - Reasoning
reasoning - Temperature
temperature
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DeepSeek-V3.2 questions
How much does the DeepSeek-V3.2 API cost?
$0.28 per million input tokens and $0.42 per million output tokens. The estimator on this page turns that into a monthly bill for your own workload.
What is the context window of DeepSeek-V3.2?
128,000 tokens of input, and it can write up to 128,000 tokens in one reply. As a rough guide, a million tokens is around 750,000 English words.
Does DeepSeek-V3.2 support tool calling?
Yes. It accepts tool definitions, which is what an agent needs to call your APIs.
Is DeepSeek-V3.2 open source?
Its weights are published, so you can run it on your own hardware or a cloud of your choice. Read the license before commercial use.
When was DeepSeek-V3.2 released?
Dec 1, 2025, with training data up to Jul 2024.
Catalog data from models.dev (MIT licensed), refreshed daily, last on Oct 15, 2026. The summary is written from these facts.