DeepSeek

DeepSeek V3.2

Public pricingMedium memoryTool use

DeepSeek V3.2 is DeepSeek's medium-memory model with tool use. This page shows current pricing, an interactive cost calculator, and a side-by-side with similar models.

Input

$0.27/1M tokens

Output

$1.10/1M tokens

Cached

$0.07/1M tokens

Batch

—

Interactive

Calculate your DeepSeek V3.2 bill.

Adjust the workload below and watch the monthly cost update in real time.

What would DeepSeek V3.2 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

DeepSeek V3.2 at a glance.

Memory

128,000

tokens

Max reply

8,192

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

deepseek

Released

—

Training cutoff

—

Availability

Public pricing

Status

active

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick DeepSeek V3.2

  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.
  • Code generation, review, or refactoring.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

DeepSeek V3.2 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, DeepSeek V3.2 costs roughly $64 per month. Input is $0.27 /1M tokens and output is $1.10 /1M tokens.
DeepSeek V3.2 has a 128,000-token context window (medium memory — a long report or a codebase file). That means you can fit about 24,000 words of input and history in a single call.
Beyond text generation, DeepSeek V3.2 supports calling functions / tools. It streams replies by default.
Models in a similar class include DeepSeek V3, Qwen 2.5, devstral-small-2505. The "Similar models" section below this FAQ links into each.

Still unsure?

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