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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.

料金

従量課金

初期費用なし、使った分だけお支払い

入力$0.17 / M Tokens
出力$0.34 / M Tokens

API 利用

以下のコード例を使用して API と連携してください:

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)

モデル紹介

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

情報

プロバイダーdeepseek
タイプllm

対応機能

入力
テキスト
出力
テキスト
コンテキスト1,048,576
最大出力384,000
Vision-
Function Calling✓ 対応

API アクセスガイド

Base URLhttps://llm.wavespeed.ai/v1
API エンドポイントchat/completions
モデル 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.

入力

$0.17 /M

出力

$0.34 /M

コンテキスト

1049K

最大出力

384K

ツール利用

対応

WaveSpeedAIでDeepSeek V4 Flashを試す

統合APIを通じてDeepSeek V4 Flashにアクセス — OpenAI互換、コールドスタートなし、透明な料金。

Playgroundを開く

DeepSeek V4 Flashに関するよくある質問

DeepSeek V4 Flash API の料金はいくらですか?+

WaveSpeedAI の料金: 入力 100 万トークンあたり $0.17、出力 100 万トークンあたり $0.34。プロンプトキャッシュとバッチ処理は別途料金で、長く反復的なワークロードでは実効コストを下げられます。

DeepSeek V4 Flash のコンテキストウィンドウはどのくらいですか?+

DeepSeek V4 Flash はリクエストあたり最大 1049K のコンテキストトークンと最大 384K の出力トークンをサポートします。

DeepSeek V4 Flash は OpenAI 互換ですか?+

はい。WaveSpeedAI は OpenAI 互換エンドポイント https://llm.wavespeed.ai/v1 で DeepSeek V4 Flash を提供します。公式 OpenAI SDK のベース URL をこちらに変更し WaveSpeedAI の API キーを設定するだけで利用可能です。

DeepSeek V4 Flash を使い始めるには?+

WaveSpeedAI にサインインし、Access Keys で API キーを作成して、上に表示されているモデル ID を指定して https://llm.wavespeed.ai/v1/chat/completions にリクエストを送信してください。新規アカウントには DeepSeek V4 Flash を試用できる無料クレジットが付与されます。

関連 LLM API