Deepseek_v41 763B parameter (FP8) model with 1,048,576 token context window.
Deepseek v4.1 flash delivers enterprise-grade performance designed for complex reasoning tasks within the Deepseek_v41 family. With 763 billion parameters quantized to FP8, this thinking model handles massive datasets effortlessly using its 1,048,576 token context window. Developers can integrate this powerhouse immediately via our standard API endpoints, ensuring your first successful call happens within minutes of reading our documentation. The architecture supports seamless switching between standard completion and extended reasoning modes, making it ideal for building sophisticated agents or analyzing lengthy codebases without fragmentation.
For researchers and technical leaders, deepseek v4.1 flash demonstrates superior benchmarks in both Arabic and English natural language understanding compared to similar alternatives in its class. It is production-ready out of the box, offering stable latency and high throughput for critical applications. We provide transparent pricing structures compatible with regional currency preferences, ensuring cost predictability for scaling operations. Whether you are validating hypotheses or deploying customer-facing solutions, the model's dual-language proficiency and robust safety alignments meet strict enterprise requirements without needing additional fine-tuning. Access requires only a starter tier account, unlocking immediate value for your pipeline.
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-v4.1-flash",
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-v4.1-flash",
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-v4.1-flash",
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-v4.1-flash",
"messages": [
{"role": "user", "content": "Hello!"}
]
}'