Cobrado pelos tokens realmente utilizados; a parte não utilizada da reserva é reembolsada.
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10 créditos grátis (US$ 0,10) ao se inscrever com Google
Utilizável 24 horas após inscrição, até 5 execuções por dia e no máximo 2 créditos por execução. Outros métodos de login começam sem créditos. Suficiente para 66 execuções deste modelo.
02
Sobre DeepSeek V4 Flash
ResumoA partir de 23 de setembro de 2026
DeepSeek V4 Flash é um modelo de DeepSeek na categoria Texto e chat. No Railwail, DeepSeek V4 Flash custa US$ 0,36 por 1M tokens de entrada e US$ 1,44 por 1M tokens de saída. A janela de contexto contém 1.048.575 tokens, e uma resposta pode ter até 384.000 tokens. Versão mais recente: DeepSeek V4.1 Flash.
DeepSeek-V4-Flash is the cost-efficient sibling of V4-Pro, released April 2026 as part of the V4 Preview. 284B total / 13B active MoE parameters with the same 1M-token context window. Designed for high-throughput agentic loops, RAG and batch tasks where latency and cost matter more than raw capability. Recommended for production agents, classification at scale, large-scale data extraction.
Fundo
Sobre DeepSeek AI
Fundado em 2023 · Hangzhou, China
DeepSeek AI is a Chinese AI research lab founded in 2023 by Liang Wenfeng, founder of the High-Flyer quantitative hedge fund. The lab is funded primarily by High-Flyer's profits. Its mission is open frontier AI, with all flagship models released with open weights. Major releases include DeepSeek LLM (2023), DeepSeek-V2 (May 2024), DeepSeek-V3 (December 2024), DeepSeek-R1 (January 2026), DeepSeek V3.1 (early 2026) and the DeepSeek V4 family (April 24, 2026), comprising V4-Pro and V4-Flash. DeepSeek is credited with popularising large-scale Reinforcement Learning from Verifiable Rewards and consistently tops open-weights leaderboards.
DeepSeek-V4-Flash was released April 24, 2026 as the efficiency-optimized sibling of V4-Pro. It is a Sparse MoE Transformer with 284B total parameters and 13B activated per token, retaining the full 1M-token native context window and 384K-token max output of the Pro variant at significantly lower inference cost. The model uses the same DeepSeek architectural stack: Multi-head Latent Attention (MLA), DeepSeekMoE with fine-grained expert specialization and shared experts, and FP8 mixed-precision training. Post-training combined supervised fine-tuning, RLVR on math/code/tool-use trajectories, and heavy distillation from the V4-Pro teacher model. V4 Flash is published with open weights under a permissive license and is designed for production-scale RAG, agentic loops and high-throughput workloads. At $0.112 input / $0.224 output per million tokens it undercuts every Western frontier model by an order of magnitude.
Parâmetros
284B total / 13B active per token
Contexto
1.048.575 tokens
Capacidades
1M token native context window with 384K max output
284B MoE / 13B active parameters
Ultra-low pricing ($0.112 / $0.224 per million tokens)
Distilled from DeepSeek V4-Pro teacher model
FP8-trained for compute efficiency
Multi-head Latent Attention for memory-efficient long context
Function calling and structured JSON output
Strong on math, STEM and coding for its size
Available via DeepSeek API, OpenRouter, Together and self-hosted with vLLM/SGLang
Open weights under a permissive license
Best for: production agents, RAG pipelines, high-throughput data extraction, on-premise inference under tight cost budgets.
Treinamento & licença
Pretrained on the same multi-trillion-token mixture as V4-Pro. Post-training combines supervised fine-tuning, RLVR and distillation from the V4-Pro teacher model. Knowledge cutoff approximately early 2026.
Licença: Open weights under a permissive license that allows commercial use. Hosted API access via deepseek.com.
Testes de segurança: DeepSeek publishes model cards but provides limited external red-teaming. Safety filters are lighter than Western frontier labs; deployers are responsible for downstream alignment.
Limitações conhecidas
Below V4-Pro on the hardest reasoning and coding benchmarks
Light built-in safety alignment relative to Western frontier models
No native vision or audio input (text-only)
Older deepseek-chat / deepseek-reasoner endpoints will be deprecated July 24, 2026
curl https://railwail.com/api/v1/chat/completions \
-H "Authorization: Bearer $RAILWAIL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-flash",
"messages": [
{
"role": "user",
"content": "Explain what a vector database is in two sentences."
}
],
"max_tokens": 1024
}'
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["RAILWAIL_API_KEY"],
base_url="https://railwail.com/api/v1",
)
completion = client.chat.completions.create(
model="deepseek-v4-flash",
messages=[
{
"role": "user",
"content": "Explain what a vector database is in two sentences.",
},
],
max_tokens=1024,
)
print(completion.choices[0].message.content)
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.RAILWAIL_API_KEY,
baseURL: "https://railwail.com/api/v1",
});
const completion = await client.chat.completions.create({
model: "deepseek-v4-flash",
messages: [
{
role: "user",
content: "Explain what a vector database is in two sentences."
}
],
max_tokens: 1024
});
console.log(completion.choices[0].message.content);
// npm install railwail
import railwail from "railwail";
const rw = railwail(process.env.RAILWAIL_API_KEY);
const res = await rw.chat("deepseek-v4-flash", [
{ role: "user", content: "Explain what a vector database is in two sentences." },
], { max_tokens: 1024 });
console.log(res.choices[0].message.content);
DeepSeek V4 Flash é um modelo de DeepSeek na categoria Texto e chat. No Railwail você pode chamá-lo com uma chave de API através da API Railwail.
Quanto custa DeepSeek V4 Flash no Railwail?
No Railwail, DeepSeek V4 Flash custa US$ 0,36 por 1M tokens de entrada e US$ 1,44 por 1M tokens de saída. Você é cobrado pelo que cada solicitação realmente usa. O uso é pago com créditos pré-pagos; 1 crédito equivale a US$ 0,01.
Qual é a janela de contexto de DeepSeek V4 Flash?
A janela de contexto de DeepSeek V4 Flash contém 1.048.575 tokens. Uma resposta pode ter até 384.000 tokens.
Qual é a velocidade de DeepSeek V4 Flash?
No Railwail, o tempo de execução mediano de DeepSeek V4 Flash nos últimos 90 dias foi 1,3 s, com base em 15 execuções concluídas.
DeepSeek V4 Flash é melhor que DeepSeek V4.1 Flash?
Depende da tarefa. DeepSeek V4 Flash (DeepSeek) e DeepSeek V4.1 Flash (DeepSeek) são ambos modelos na categoria Texto e chat. A página de comparação mostra seus preços e especificações lado a lado.
Crie uma chave de API Railwail e envie sua solicitação com o ID do modelo deepseek-v4-flash. Exemplos de código para curl, Python e JavaScript estão na seção API desta página.
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