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deepseek
deepseek/deepseek-v4-flash

deepseek/deepseek-v4-flash

1,048,576 context · $0.17/M input tokens · $0.34/M output tokens

DeepSeek V4 Flash is DeepSeek's efficiency-first open-source model released in April 2026, built on a 284B-parameter Mixture-of-Experts architecture with just 13B parameters active per token — the smallest activation footprint among current Tier-1 models. It shares the same 1M-token context window and hybrid attention design as V4 Pro, delivering near-equivalent reasoning capability (LiveCodeBench 91.6, Codeforces 3052, SWE-bench Verified 79.0) while running significantly faster and at dramatically lower cost. Pre-trained on 32T tokens, V4 Flash is purpose-built for high-throughput, latency-sensitive scenarios such as coding assistants, conversational agents, and batch processing pipelines. It supports thinking and non-thinking modes, function calling, JSON output, and FIM completion.

가격

사용량 기반 과금

선결제 없이 사용한 만큼만 지불

입력$0.17 / M Tokens
출력$0.34 / M Tokens

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-v4-flash",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

모델 소개

Deepseek deepseek-v4-flash

DeepSeek-V4-Flash is DeepSeek's cost-efficient open-source model, released on April 24, 2026. It is a 284B parameter Mixture-of-Experts (MoE) language model with only 13B active parameters, pre-trained on 32T tokens, supporting a context length of one million tokens. V4-Flash delivers reasoning performance approaching V4-Pro while being significantly faster and cheaper — making it ideal for high-volume, latency-sensitive workloads.


Why It Looks Great

  • Mixture-of-Experts architecture with 284B total parameters and only 13B active — the smallest activation among Tier-1 models
  • 1000000 context window powered by Compressed Sparse Attention (CSA) and DeepSeek Sparse Attention (DSA)
  • Near V4-Pro reasoning performance at a fraction of the cost

Key Features

  • Context Window: 1000000 tokens
  • Max Output: 384000 tokens
  • Vision: Not Supported
  • Function Calling: Supported
  • Thinking Mode: Supported (non-thinking / high / max)
  • JSON Output: Supported
  • FIM Completion: Supported (non-thinking mode only)

Benchmarks

BenchmarkV4-FlashV4-ProClaude Opus 4.6GPT-5.4
SWE-bench Verified79.080.680.8
LiveCodeBench91.693.588.891.7
Codeforces Rating305232063168
MMLU-Pro86.287.589.187.5
Terminal Bench 2.056.967.965.475.1

Specifications

SpecificationValue
ProviderDeepseek
Model TypeLarge Language Model (LLM)
ArchitectureMixture-of-Experts (MoE)
Total Parameters284B (13B active)
Context Window1000000 tokens
Max Output384000 tokens
InputText
OutputText
VisionNot Supported
Function CallingSupported
Thinking ModeSupported (high / max)
Release DateApril 24, 2026

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-v4-flash


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-v4-flash",
    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-v4-flash",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: deepseek/deepseek-v4-flash
  • Provider: Deepseek
  • Open-source weights available on HuggingFace and ModelScope
  • Supports both OpenAI and Anthropic API formats
  • For simple Agent tasks, V4-Flash performs on par with V4-Pro; for complex agentic workflows, consider V4-Pro

정보

제공자deepseek
유형llm

지원 기능

입력
텍스트
출력
텍스트
컨텍스트1,048,576
최대 출력384,000
Vision-
Function Calling✓ 지원

API 접근 가이드

Base URLhttps://llm.wavespeed.ai/v1
API 엔드포인트chat/completions
모델 IDdeepseek/deepseek-v4-flash

DeepSeek V4 Flash API

deepseek/deepseek-v4-flash

DeepSeek V4 Flash is DeepSeek's efficiency-first open-source model released in April 2026, built on a 284B-parameter Mixture-of-Experts architecture with just 13B parameters active per token — the smallest activation footprint among current Tier-1 models. It shares the same 1M-token context window and hybrid attention design as V4 Pro, delivering near-equivalent reasoning capability (LiveCodeBench 91.6, Codeforces 3052, SWE-bench Verified 79.0) while running significantly faster and at dramatically lower cost. Pre-trained on 32T tokens, V4 Flash is purpose-built for high-throughput, latency-sensitive scenarios such as coding assistants, conversational agents, and batch processing pipelines. It supports thinking and non-thinking modes, function calling, JSON output, and FIM completion.

입력

$0.17 /M

출력

$0.34 /M

컨텍스트

1049K

최대 출력

384K

도구 사용

지원

WaveSpeedAI에서 DeepSeek V4 Flash 체험

통합 API를 통해 DeepSeek V4 Flash 액세스 — OpenAI 호환, 콜드 스타트 없음, 투명한 가격.

Playground 열기

DeepSeek V4 Flash에 대해 자주 묻는 질문

DeepSeek V4 Flash API 비용은 얼마인가요?+

WaveSpeedAI 가격: 입력 토큰 100만 개당 $0.17, 출력 토큰 100만 개당 $0.34. 프롬프트 캐싱과 배치 처리는 별도로 청구되며 긴 반복 작업에서 실질 비용을 줄여 줍니다.

DeepSeek V4 Flash의 컨텍스트 윈도우는 얼마나 되나요?+

DeepSeek V4 Flash은 요청당 최대 1049K 컨텍스트 토큰과 최대 384K 출력 토큰을 지원합니다.

DeepSeek V4 Flash은 OpenAI 호환인가요?+

네. WaveSpeedAI는 OpenAI 호환 엔드포인트 https://llm.wavespeed.ai/v1을 통해 DeepSeek V4 Flash을 제공합니다. 공식 OpenAI SDK의 base URL을 이 주소로 변경하고 WaveSpeedAI API 키를 사용하면 코드 변경 없이 사용할 수 있습니다.

DeepSeek V4 Flash을 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 V4 Flash을 평가할 수 있는 무료 크레딧을 받습니다.

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