Deepseek4 304B parameter (FP8) model with 1,048,576 token context window.
Deepseek v4 flash 0731 delivers enterprise-grade reasoning within the Deepseek4 family. Built with 304B parameters and FP8 quantization, this thinking model handles complex logical tasks efficiently. The massive 1,048,576 token context window allows developers to process entire codebases or lengthy documentation in a single pass. Integration is streamlined for API builders, enabling your first successful call within minutes using standard endpoints. Whether you are building agentic workflows or analyzing large datasets, the architecture ensures low-latency inference without compromising on depth.
Researchers will find robust performance across bilingual tasks, with optimized capabilities for both Arabic and English workflows. While specific benchmark tables are available in our detailed documentation, this model consistently outperforms alternatives in reasoning-heavy scenarios. For business decision makers, the model is production-ready and accessible on the starter tier. Operating at a 2x credit multiplier relative to the base rate, it offers a cost-effective balance between high-end intelligence and operational budget. You can deploy confidently knowing the platform supports seamless scaling for high-volume applications without hidden infrastructure complexities.
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:0731",
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:0731",
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:0731",
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:0731",
"messages": [
{"role": "user", "content": "Hello!"}
]
}'