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deepseek/deepseek-v3.2-exp

deepseek/deepseek-v3.2-exp

출시일: 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...

가격

사용량 기반 과금

선결제 없이 사용한 만큼만 지불

입력$0.27 / M Tokens
출력$0.41 / M Tokens

모델 사용해 보기

deepseek/deepseek-v3.2-exp
온라인
deepseek
안녕하세요! 도움이 되는 AI 어시스턴트입니다. 무엇을 도와드릴까요?

API 사용법

다음 코드 예시를 사용해 API와 연동하세요:

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)

모델 소개

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

정보

제공자deepseek
유형llm

지원 기능

입력
텍스트
출력
텍스트
컨텍스트163,840
최대 출력65,536
Vision-
Function Calling✓ 지원

API 접근 가이드

Base URLhttps://llm.wavespeed.ai/v1
API 엔드포인트chat/completions
모델 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...

입력

$0.27 /M

출력

$0.41 /M

컨텍스트

164K

최대 출력

66K

도구 사용

지원

WaveSpeedAI에서 DeepSeek V3.2 Exp 체험

통합 API를 통해 DeepSeek V3.2 Exp 액세스 — OpenAI 호환, 콜드 스타트 없음, 투명한 가격.

DeepSeek V3.2 Exp에 대해 자주 묻는 질문

DeepSeek V3.2 Exp API 비용은 얼마인가요?+

WaveSpeedAI 가격: 입력 토큰 100만 개당 $0.27, 출력 토큰 100만 개당 $0.41. 프롬프트 캐싱과 배치 처리는 별도로 청구되며 긴 반복 작업에서 실질 비용을 줄여 줍니다.

DeepSeek V3.2 Exp의 컨텍스트 윈도우는 얼마나 되나요?+

DeepSeek V3.2 Exp은 요청당 최대 164K 컨텍스트 토큰과 최대 66K 출력 토큰을 지원합니다.

DeepSeek V3.2 Exp은 OpenAI 호환인가요?+

네. WaveSpeedAI는 OpenAI 호환 엔드포인트 https://llm.wavespeed.ai/v1을 통해 DeepSeek V3.2 Exp을 제공합니다. 공식 OpenAI SDK의 base URL을 이 주소로 변경하고 WaveSpeedAI API 키를 사용하면 코드 변경 없이 사용할 수 있습니다.

DeepSeek V3.2 Exp을 어떻게 시작하나요?+

WaveSpeedAI에 로그인하고 Access Keys에서 API 키를 만든 다음, 위에 표시된 모델 ID로 https://llm.wavespeed.ai/v1/chat/completions에 요청을 보내세요. 신규 계정은 DeepSeek V3.2 Exp을 평가할 수 있는 무료 크레딧을 받습니다.

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