Fatturato in base ai token effettivamente utilizzati; la parte inutilizzata della prenotazione viene rimborsata.
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10 crediti gratuiti (0,10 USD) quando ti iscrivi con Google
Utilizzabile 24 ore dopo l'iscrizione, fino a 5 esecuzioni al giorno e al massimo 2 crediti per esecuzione. Altri metodi di accesso iniziano senza crediti. Sufficiente per 66 esecuzioni di questo modello.
02
Informazioni su DeepSeek V4 Flash
RiassuntoA partire da 23 settembre 2026
DeepSeek V4 Flash è un modello di DeepSeek nella categoria Testo e chat. Su Railwail, DeepSeek V4 Flash costa 0,36 USD per 1M token di input e 1,44 USD per 1M token di output. La finestra di contesto contiene 1.048.575 token e una risposta può essere lunga fino a 384.000 token. Versione più 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.
Sfondo
Informazioni su DeepSeek AI
Fondato 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.
Parametri
284B total / 13B active per token
Contesto
1.048.575 token
Capacità
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.
Addestramento e licenza
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.
Licenza: Open weights under a permissive license that allows commercial use. Hosted API access via deepseek.com.
Test di sicurezza: DeepSeek publishes model cards but provides limited external red-teaming. Safety filters are lighter than Western frontier labs; deployers are responsible for downstream alignment.
Limitazioni note
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 è un modello di DeepSeek nella categoria Testo e chat. Su Railwail puoi richiamarlo con una chiave API tramite l'API Railwail.
Quanto costa DeepSeek V4 Flash su Railwail?
Su Railwail, DeepSeek V4 Flash costa 0,36 USD per 1M token di input e 1,44 USD per 1M token di output. Ti viene addebitato ciò che ogni richiesta utilizza effettivamente. L'utilizzo viene pagato con crediti prepagati; 1 credito equivale a 0,01 USD.
Qual è la finestra di contesto di DeepSeek V4 Flash?
La finestra di contesto di DeepSeek V4 Flash contiene 1.048.575 token. Una risposta può essere lunga fino a 384.000 token.
Quanto è veloce DeepSeek V4 Flash?
Non ci sono ancora abbastanza esecuzioni misurate di DeepSeek V4 Flash su Railwail per indicare un tempo di esecuzione. Dipende dall'input, dalle impostazioni e dal carico presso il provider.
DeepSeek V4 Flash è migliore di DeepSeek V4.1 Flash?
Dipende dall'attività. DeepSeek V4 Flash (DeepSeek) e DeepSeek V4.1 Flash (DeepSeek) sono entrambi modelli nella categoria Testo e chat. La pagina di confronto mostra i loro prezzi e le specifiche affiancati.
Crea una chiave API Railwail e invia la tua richiesta con l'ID modello deepseek-v4-flash. Gli esempi di codice per curl, Python e JavaScript sono nella sezione API di questa pagina.
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