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deepseek
deepseek/deepseek-v3.2-exp

deepseek/deepseek-v3.2-exp

प्रकाशन तिथि: 2025-09-29

163,840 context · $0.27/M input tokens · $0.41/M output tokens

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input$0.27 / M Tokens
Output$0.41 / M Tokens

Try the model

deepseek/deepseek-v3.2-exp
Online
deepseek
Hi! I am a helpful AI assistant. What can I do for you?

API Usage

Use the following code examples to integrate with our API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v3.2-exp",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Model Introduction

Deepseek deepseek-v3.2-exp

DeepSeek-V3

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism designed to improve training and inference efficiency in long-context scenarios while maintaining output quality. Users can control the reasoning behaviour with the reasoning enabled boolean. Learn more in our docs

The model was trained under conditions aligned with V3.1-Terminus to enable direct comparison. Benchmarking shows performance roughly on par with V3.1 across reasoning, coding, and agentic tool-use tasks, with minor tradeoffs and gains depending on the domain. This release focuses on validating architectural optimizations for extended context lengths rather than advancing raw task accuracy, making it primarily a research-oriented model for exploring e


Why It Looks Great

  • Large Language Model architecture for efficient processing
  • 163840 context window for long document handling
  • Competitive pricing at $0.3/$0.4 per million tokens

Key Features

  • Context Window: 163840 tokens
  • Max Output: 65536 tokens
  • Vision: Supported
  • Function Calling: Supported

Specifications

SpecificationValue
ProviderDeepseek
Model TypeLarge Language Model (LLM)
ArchitectureN/A
Context Window163840 tokens
Max Output65536 tokens
InputText
OutputText
VisionSupported
Function CallingSupported

Pricing

Token TypeCost per Million Tokens
Input$0.3
Output$0.4

How to Use

  1. Write your prompt — describe the task, provide context, and specify desired output format.
  2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-v3.2-exp


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-v3.2-exp",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek/deepseek-v3.2-exp",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: deepseek/deepseek-v3.2-exp
  • Provider: Deepseek

Info

Providerdeepseek
Typellm

Supported Functionality

Input
Text
Output
Text
Context163,840
Max Output65,536
Vision-
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDdeepseek/deepseek-v3.2-exp

DeepSeek V3.2 Exp API

deepseek/deepseek-v3.2-exp

DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...

Input

$0.27 /M

Output

$0.41 /M

Context

164K

Max Output

66K

Tool Use

Supported

Try DeepSeek V3.2 Exp on WaveSpeedAI

Access DeepSeek V3.2 Exp through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about DeepSeek V3.2 Exp

How much does DeepSeek V3.2 Exp cost via the API?+

Pricing on WaveSpeedAI: $0.27 per million input tokens and $0.41 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of DeepSeek V3.2 Exp?+

DeepSeek V3.2 Exp supports up to 164K tokens of context with up to 66K tokens of output per request.

Is DeepSeek V3.2 Exp OpenAI-compatible?+

Yes. WaveSpeedAI exposes DeepSeek V3.2 Exp through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.

How do I get started with DeepSeek V3.2 Exp?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate DeepSeek V3.2 Exp before paying per token.

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