deepseek/deepseek-v4-flash
Data publikacji: 2026-04-24
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.
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Użyj poniższych przykładów kodu, aby zintegrować się z naszym API:
import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'deepseek/deepseek-v4-flash',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}import OpenAI from 'openai';
if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
apiKey: process.env.WAVESPEED_API_KEY,
baseURL: 'https://llm.wavespeed.ai/v1',
timeout: 120_000,
maxRetries: 2,
});
try {
const response = await client.chat.completions.create({
model: 'deepseek/deepseek-v4-flash',
messages: [{ role: 'user', content: 'Hello!' }],
});
console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
console.error('LLM request failed:', error);
process.exitCode = 1;
}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.
| Benchmark | V4-Flash | V4-Pro | Claude Opus 4.6 | GPT-5.4 |
|---|---|---|---|---|
| SWE-bench Verified | 79.0 | 80.6 | 80.8 | — |
| LiveCodeBench | 91.6 | 93.5 | 88.8 | 91.7 |
| Codeforces Rating | 3052 | 3206 | — | 3168 |
| MMLU-Pro | 86.2 | 87.5 | 89.1 | 87.5 |
| Terminal Bench 2.0 | 56.9 | 67.9 | 65.4 | 75.1 |
| Specification | Value |
|---|---|
| Provider | Deepseek |
| Model Type | Large Language Model (LLM) |
| Architecture | Mixture-of-Experts (MoE) |
| Total Parameters | 284B (13B active) |
| Context Window | 1000000 tokens |
| Max Output | 384000 tokens |
| Input | Text |
| Output | Text |
| Vision | Not Supported |
| Function Calling | Supported |
| Thinking Mode | Supported (high / max) |
| Release Date | April 24, 2026 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: deepseek/deepseek-v4-flash
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 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!"}]
}'
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
Uzyskaj dostęp do DeepSeek V4 Flash przez nasze ujednolicone API — kompatybilne z OpenAI, bez zimnych startów, przejrzyste ceny.
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.
DeepSeek V4 Flash obsługuje do 1049K tokenów kontekstu i do 384K tokenów wyjściowych na zapytanie.
WaveSpeedAI udostępnia DeepSeek V4 Flash pod adresem https://llm.wavespeed.ai/v1 przez interfejs Chat Completions zgodny z OpenAI. W większości klientów OpenAI SDK wystarczy zmienić base URL i klucz API; opcjonalne pola zależą od modelu.
Zaloguj się do WaveSpeedAI, utwórz klucz API w Access Keys i wyślij żądanie do https://llm.wavespeed.ai/v1/chat/completions z identyfikatorem modelu pokazanym powyżej. Bieżącą dostępność, możliwości i ceny sprawdź w katalogu modeli.