Seedance 2.0 | Special Offer ✦ 10% OFF NOW
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.

Cennik

Płać za użycie

Bez kosztów początkowych, płacisz tylko za to, czego używasz

Wejście$0.17 / M Tokens
Wyjście$0.34 / M Tokens

Użycie API

Użyj poniższych przykładów kodu, aby zintegrować się z naszym 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-v4-flash",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Wprowadzenie do modelu

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

Info

Dostawcadeepseek
Typllm

Obsługiwane funkcje

Wejście
Tekst
Wyjście
Tekst
Kontekst1,048,576
Maks. wyjście384,000
Vision-
Function Calling✓ Obsługiwane

Przewodnik dostępu do API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID modeludeepseek/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.

Wejście

$0.17 /M

Wyjście

$0.34 /M

Kontekst

1049K

Maks. wyjście

384K

Użycie narzędzi

Obsługiwane

Wypróbuj DeepSeek V4 Flash w WaveSpeedAI

Uzyskaj dostęp do DeepSeek V4 Flash przez nasze ujednolicone API — kompatybilne z OpenAI, bez zimnych startów, przejrzyste ceny.

Otwórz Playground

Najczęstsze pytania o DeepSeek V4 Flash

Ile kosztuje API DeepSeek V4 Flash?+

Cennik na WaveSpeedAI: $0.17 za milion tokenów wejściowych i $0.34 za milion tokenów wyjściowych. Prompt caching i przetwarzanie wsadowe są rozliczane oddzielnie i obniżają efektywny koszt długich, powtarzalnych obciążeń.

Jakie jest okno kontekstu DeepSeek V4 Flash?+

DeepSeek V4 Flash obsługuje do 1049K tokenów kontekstu i do 384K tokenów wyjściowych na zapytanie.

Czy DeepSeek V4 Flash jest kompatybilny z OpenAI?+

Tak. WaveSpeedAI udostępnia DeepSeek V4 Flash przez endpoint kompatybilny z OpenAI pod https://llm.wavespeed.ai/v1. Skieruj oficjalny OpenAI SDK na ten base URL ze swoim kluczem API WaveSpeedAI — bez innych zmian w kodzie.

Jak zacząć z DeepSeek V4 Flash?+

Zaloguj się do WaveSpeedAI, utwórz klucz API w Access Keys, a następnie wyślij żądanie na https://llm.wavespeed.ai/v1/chat/completions z id modelu pokazanym powyżej. Nowe konta otrzymują darmowe kredyty na ocenę DeepSeek V4 Flash.

Powiązane API LLM