DeepSeek V3 API

DeepSeek V3 is the latest version of the large language model from DeepSeek. Contrary to its predecessors, DeepSeek V3 is introducing 685 billion parameters, a Mixture of Experts architecture with 256 experts, increased vocabulary size, expanded hidden layers, and extended position embeddings. For benchmarks, it is pretty impressive: 48.4% on the Aider Polyglot leaderboard and leading several prominent models. DeepSeek V3 currently starts being deployed step-by-step using chat.deepseek.com and the DeepSeek API; thus, being quite well-positioned on active competitor analysis among higher artificial intelligence language models.

import OpenAI from "openai"

const openai = new OpenAI({
  baseURL: "https://api.aiapilab.com/v1",
  apiKey: $AIAPILAB_API_KEY
})

async function main() {
  const completion = await openai.chat.completions.create({
    model: "deepseek-chat",
    messages: [
      {
        "role": "user",
        "content": "Write a blog about cat."
      }
    ]
  })

  console.log(completion.choices[0].message)
}
main()

from openai import OpenAI

client = OpenAI(
  base_url="https://api.aiapilab.com/v1",
  api_key="$AIAPILAB_API_KEY",
)

completion = client.chat.completions.create(
  model="deepseek-chat",
  messages=[
    {
      "role": "user",
      "content": "Write a blog about cat."
    }
  ]
)
print(completion.choices[0].message.content)

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DeepSeek V3 API Pricing (per million token)

Context65536

Input$0.15 / M

Output$0.3 / M

Description

DeepSeek V3 is the newest version of the large language model developed at DeepSeek, representing an enormous improvement in AI capability. This model has as many as 685 billion parameters, one of the largest publicly known models in the world. DeepSeek V3 uses a Mixture of Experts architecture: 256 experts, each activating 8 per token to bring about better performance and efficiency. DeepSeek V3 has performed fantastically on many benchmarks: DeepSeek V3 scored 48.4% in the Aider Polyglot leaderboard, which is second only to O1 and above other famous models such as Claude 3 Sonnet and Gemini, showing that DeepSeek V3 will do great on many programming languages and tasks.
Access to this model is presently being granted via a gradual rollout through chat.deepseek.com and the AIAPILAB. As this development continues to roll out, DeepSeek V3 will become another entrant into the ranks of large language models with increased functionality for a number of use cases.

Model API Use Case

The DeepSeek V3 API empowers developers and businesses to integrate advanced AI capabilities into their workflows. Here are some of the primary use cases:

Code Generation and Assistance: Developers can use DeepSeek V3 to generate code snippets across multiple programming languages, debug existing code, optimize algorithms, and provide code reviews and suggestions. For example, a team improved project delivery time by automating repetitive coding tasks with DeepSeek V3.

Natural Language Processing: DeepSeek V3 excels in content creation, text summarization, sentiment analysis, and language translation. These capabilities enable businesses to generate high-quality articles, analyze user feedback, and monitor social media more efficiently.

Data Analysis and Visualization: The API assists in interpreting complex datasets, generating actionable insights, and creating scripts for data visualization and machine learning tasks, helping organizations streamline their data workflows.

Chatbot and Virtual Assistant Development: DeepSeek V3's conversational abilities make it ideal for building advanced chatbots for customer service, creating virtual assistants for task automation, and developing interactive learning platforms.

Creative Writing and Content Creation: Content creators can leverage DeepSeek V3 for generating creative prompts, assisting with story development and plot ideas, and creating engaging marketing copy or slogans.

Technical Documentation: DeepSeek V3 simplifies the generation of API documentation, user manuals, and technical guides, while also breaking down complex technical concepts into easy-to-understand language.

By integrating DeepSeek V3, users can enhance productivity, reduce errors, and unlock innovative solutions across a variety of applications.

Model Review

Pros

1. Exceptional performance in coding and reasoning tasks, outperforming competitors in key benchmarks. 2. Advanced Mixture of Experts (MoE) architecture with 256 experts, optimizing both efficiency and accuracy. 3. Extensive training on 2 trillion tokens across 80+ programming languages, ensuring versatility and compatibility. 4. Competitive pricing starting at $0.14 per 1 million input tokens, making it accessible for various use cases. 5. Staged rollout ensures high-quality service and gradual scalability for users.

Cons

1. The DeepSeek V3 model requires substantial computational resources, which may limit access for smaller organizations or individual users. 2. The model is still undergoing a staged rollout, meaning full access is not available to all users yet. 3. As one of the largest models, it may introduce complexities in deployment and integration for new users.

Comparison

Feature/Aspect	GPT-4o	DeepSeek V3	Claude 3.5 Sonnet
Parameters	Not disclosed	685 billion	Not disclosed
Architecture	Not disclosed	Mixture of Experts (256 experts)	Not disclosed
Availability	Available via API and ChatGPT	Gradual rollout via API and chat platform	Available via API and web interface
Context Window	8,192 tokens	4,096 tokens	200,000 tokens
HumanEval Score	90.2%	89%	92%
Aider Polyglot Score	Not available	48.4%	Not available
Pricing (per 1M tokens)	$2.50 (input) / $10.00 (output)	$0.15 (input) / $0.3 (output)	$3.00 (input) / $15.00 (output)
Specialized Capabilities	General and writing capabilities	Strong in coding and general tasks	Advanced reasoning, conversation, coding

API

import OpenAI from "openai"

const openai = new OpenAI({
  baseURL: "https://api.aiapilab.com/v1",
  apiKey: $AIAPILAB_API_KEY
})

async function main() {
  const completion = await openai.chat.completions.create({
    model: "deepseek-chat",
    messages: [
      {
        "role": "user",
        "content": "Write a blog about cat."
      }
    ]
  })

  console.log(completion.choices[0].message)
}
main()

from openai import OpenAI

client = OpenAI(
  base_url="https://api.aiapilab.com/v1",
  api_key="$AIAPILAB_API_KEY",
)

completion = client.chat.completions.create(
  model="deepseek-chat",
  messages=[
    {
      "role": "user",
      "content": "Write a blog about cat."
    }
  ]
)
print(completion.choices[0].message.content)

FAQ

Q1: What is DeepSeek V3?  
A1: DeepSeek V3 is the latest large language model from DeepSeek, featuring 685 billion parameters and a Mixture of Experts (MoE) architecture with 256 experts. It is designed to handle advanced tasks like coding, reasoning, and multi-language support.

Q2: How does DeepSeek V3 compare to competitors?  
A2: DeepSeek V3 demonstrates strong performance across benchmarks, including 48.4% on the Aider Polyglot leaderboard, outperforming competitors like Claude 3 Sonnet and Gemini in several areas.

Q3: Where is DeepSeek V3 available?  
A3: DeepSeek V3 is currently available through a staged rollout via the DeepSeek API and their chat platform (chat.deepseek.com).

Q4: What are the main use cases of DeepSeek V3?  
A4: DeepSeek V3 excels in tasks such as code generation, debugging, natural language understanding, and data analysis. It is particularly suited for developers and businesses seeking advanced AI solutions.

Q5: How much does it cost to use DeepSeek V3?  
A5: Pricing for DeepSeek V3 starts at $0.14 per 1 million input tokens and $0.28 per 1 million output tokens. Additional costs may apply depending on usage and API features.