Deepseek4 158B parameter (FP8) model with 1,048,576 token context window.
Deepseek v4 flash preview delivers enterprise-grade performance designed for complex reasoning tasks and extensive document analysis. Built on the Deepseek4 family, this 158B parameter model utilizes FP8 quantization to balance high-speed inference with exceptional accuracy. Developers gain immediate access to a massive 1,048,576 token context window, enabling seamless processing of entire codebases or lengthy technical manuals without truncation. Integration is streamlined through our standard API endpoints, allowing you to execute your first request within minutes of signing up. The thinking category ensures rigorous logical deduction, making it ideal for agents requiring multi-step problem solving.
For researchers and technical leaders, this model demonstrates state-of-the-art capabilities across both English and Arabic linguistic tasks. Benchmark evaluations confirm superior performance in nuanced language understanding compared to similar parameter classes, ensuring reliability in production pipelines. We provide transparent credit pricing with a 2x multiplier relative to base rates, offering predictable cost management for high-volume applications. Available from the starter tier, it removes barriers to entry while maintaining the robustness required for mission-critical deployments. Our platform ensures you can verify Arabic support and cost efficiency immediately without needing to contact sales teams. Choose Deepseek v4 flash preview to leverage advanced reasoning and bilingual proficiency without compromising on scalability or budget.
from openai import OpenAI
client = OpenAI(
base_url="https://llmapi.resayil.io/v1/",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="deepseek-v4-flash:preview",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)import anthropic
client = anthropic.Anthropic(
base_url="https://llmapi.resayil.io/v1",
api_key="YOUR_API_KEY"
)
message = client.messages.create(
model="deepseek-v4-flash:preview",
max_tokens=1024,
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(message.content[0].text)const response = await fetch(
"https://llmapi.resayil.io/v1/chat/completions",
{
method: "POST",
headers: {
"Content-Type": "application/json",
"Authorization": "Bearer YOUR_API_KEY"
},
body: JSON.stringify({
model: "deepseek-v4-flash:preview",
messages: [
{ role: "user", content: "Hello!" }
]
})
}
);
const data = await response.json();
console.log(data.choices[0].message.content);curl https://llmapi.resayil.io/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "deepseek-v4-flash:preview",
"messages": [
{"role": "user", "content": "Hello!"}
]
}'