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const { OpenAI } = require('openai');
const api = new OpenAI({
baseURL: 'https://api.ai.cc/v1',
apiKey: '',
});
const main = async () => {
const result = await api.chat.completions.create({
model: 'deepseek/deepseek-chat',
messages: [
{
role: 'system',
content: 'You are an AI assistant who knows everything.',
},
{
role: 'user',
content: 'Tell me, why is the sky blue?'
}
],
});
const message = result.choices[0].message.content;
console.log(`Assistant: ${message}`);
};
main();
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.ai.cc/v1",
api_key="",
)
response = client.chat.completions.create(
model="deepseek/deepseek-chat",
messages=[
{
"role": "system",
"content": "You are an AI assistant who knows everything.",
},
{
"role": "user",
"content": "Tell me, why is the sky blue?"
},
],
)
message = response.choices[0].message.content
print(f"Assistant: {message}")
-
AI Playground
Test all API models in the sandbox environment before you integrate.
We provide more than 300 models to integrate into your app.
Product Detail
Dive into the capabilities of DeepSeek-V3, a cutting-edge large language model engineered by DeepSeek AI. This advanced model is designed to excel in natural language understanding and generation, powered by an innovative Mixture-of-Experts (MoE) architecture.
✨ DeepSeek-V3: Core Information
- Model Name: DeepSeek-V3
- Developer: DeepSeek AI
- Release Date: December 26, 2024
- Version: 1.0
- Model Type: Large Language Model (LLM)
Pricing: Input $0.0015750 | Output $0.0015750 per 1000 tokens.
💡 Key Features & Architectural Innovations
- Mixture-of-Experts (MoE) Architecture: Employs a dynamic activation mechanism that only activates the necessary parameters for each task, optimizing resource utilization and boasting 685 billion parameters with only 37 billion activated per token.
- Multi-Head Latent Attention (MLA): Enhances context understanding by extracting key details multiple times, improving accuracy and efficiency in complex scenarios.
- Multi-Token Prediction (MTP): Generates several tokens simultaneously, significantly speeding up inference and enhancing performance on complex benchmarks.
- Exceptional Performance Metrics: Achieves high scores across various benchmarks, including MMLU (87.1%), BBH (87.5%), and advanced mathematical reasoning tasks.
- Efficient Training: Required only 2.788 million GPU hours for full training, demonstrating remarkable cost-effectiveness.
🎯 Intended Use Cases
DeepSeek-V3 is designed for developers and researchers looking to implement advanced natural language processing capabilities in applications such as:
- Advanced Chatbots and Conversational AI
- Intelligent Educational Tools
- Automated Content Generation
- Sophisticated Coding Assistance
🌐 Language Support: The model offers multi-language support, enhancing its versatility across diverse linguistic contexts.
⚙️ Technical Deep Dive
Architecture Breakdown
At its core, DeepSeek-V3 utilizes a Mixture-of-Experts (MoE) architecture for efficient processing, activating only a subset of its parameters based on the task. This is further complemented by Multi-Head Latent Attention (MLA) to significantly improve context understanding.
Comprehensive Training Data
The model was trained on an expansive dataset consisting of 14.8 trillion tokens, carefully curated from diverse and high-quality texts.
- Data Source and Size: A robust collection encompassing a wide range of topics and genres for versatility.
- Diversity and Bias: The training data was rigorously curated to minimize biases while maximizing diversity in topics and styles, ensuring the model generates varied and fair outputs.
📈 Performance Metrics & Industry Comparison
DeepSeek-V3 consistently demonstrates superior performance across leading benchmarks. For a detailed visual comparison against other models, please refer to the image below:
Visual comparison of DeepSeek-V3's performance against other prominent models.
💻 Getting Started & Integration
Code Samples
DeepSeek-V3 is readily available on the AI/ML API platform under the name "DeepSeek V3". Integrate it into your applications using standard API calls.
# Example: Python API call for DeepSeek-V3
import openai
openai.api_base = "https://api.ai.cc/v1"
openai.api_key = "YOUR_API_KEY"
response = openai.chat.completions.create(
model="deepseek/deepseek-chat",
messages=[
{"role": "user", "content": "Explain the Mixture-of-Experts architecture."}
]
)
print(response.choices[0].message.content)
API Documentation
Comprehensive API Documentation is available to guide developers through seamless integration and usage.
⚖️ Ethical Guidelines & Responsible AI
DeepSeek AI places strong emphasis on ethical considerations in AI development. They advocate for transparency regarding the model's capabilities and limitations, and actively encourage responsible usage to prevent misuse or harmful applications of generated content.
📜 Licensing Information
DeepSeek-V3 is available under an open-source license. This license grants both research and commercial usage rights, while ensuring compliance with ethical standards concerning creator rights and intellectual property.
Ready to integrate DeepSeek-V3 into your next innovative project?
Get DeepSeek V3 API Access Here!❓ Frequently Asked Questions (FAQ)
1. What is DeepSeek-V3 and what makes it unique?
DeepSeek-V3 is a state-of-the-art large language model (LLM) from DeepSeek AI. Its uniqueness lies in its advanced Mixture-of-Experts (MoE) architecture, which efficiently manages 685 billion parameters by activating only 37 billion per token, ensuring high performance and efficiency in natural language tasks.
2. How does DeepSeek-V3 handle complex context and accelerate inference?
It utilizes Multi-Head Latent Attention (MLA) for enhanced context understanding and Multi-Token Prediction (MTP) to generate several tokens simultaneously, significantly speeding up inference and improving performance on complex benchmarks.
3. What are the primary applications for DeepSeek-V3?
DeepSeek-V3 is designed for developers and researchers to power advanced applications such as intelligent chatbots, educational tools, content generation platforms, and sophisticated coding assistance, leveraging its multi-language support and NLP capabilities.
4. Where can I find the API and detailed documentation for DeepSeek-V3?
The DeepSeek-V3 API is available on the AI/ML API platform. Comprehensive API Documentation can be found there, and you can obtain API access by signing up here.
5. Is DeepSeek-V3 open-source, and what are its licensing terms?
Yes, DeepSeek-V3 is released under an open-source license that permits both research and commercial usage. This ensures adherence to ethical standards concerning creator rights while fostering broad adoption and innovation.
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