Qwen 3 Coder vs DeepSeek 0324: Which Model for Which Code?

Choosing between Qwen 3 Coder and Deepseek 0324 depends on your project’s needs and coding style. Both models are powerful, multilingual AI coding assistants available via Novita AI, but they excel in different scenarios. This guide will help you decide which model is best for your coding tasks and how to get started with either one.

Qwen3 Coder vs Deepseek 0324: Task

Prompt: A detective is investigating a case involving five suspects: Alice, Ben, Carla, David, and Eva. Only one of them is guilty. The detective receives the following statements: Alice says: “Ben is guilty.” Ben says: “Carla is lying.” Carla says: “Eva is guilty.” David says: “I didn’t do it.” Eva says: “Carla is telling the truth.” Exactly one person is telling the truth. Who is guilty, and how do you know?

Qwen3 Coder vs Deepseek 0324：There is not much difference between the two in their core ability to handle logic problems, both are at a high level, but deepseek focuses more on detailed process explanations, while qwen 3 coder focuses more on efficient and concise presentation of logic.

Prompt: Write a simple snake game

Qwen3 Coder vs Deepseek 0324：Deepseek’s stronger code ability through its structured approach, feature richness, and clean separation of logic, while Qwen 3 Coder is better suited for quick prototypes or teaching beginners.

Qwen3 Coder vs Deepseek 0324: Basic Introduction

Feature	Qwen3 Coder	DeepSeek 0324
Model Size	480B parameters (35B activated, 62 layers, 160 experts, 8 activated per token)	671B parameters (37B activated per token)
Open Source	Yes	Yes
Context Length	256K tokens	128K tokens
Architecture	Mixture-of-Experts (MoE),	Mixture-of-Experts (MoE)
“Thinking” Mode	No thinking mode	No thinking mode
Language Support	100+ languages; excels in English and Chinese, leading multilingual performance	English and Chinese (excels in both)
Multimodal	Text-to-text	Text-to-text
Training Data	36T tokens from diverse sources: web, books, PDFs, synthetic code/math	14.8T tokens from diverse sources
Training Method	Large-scale RL (including Agent RL, code RL, long-horizon RL for coding tasks)	RL techniques from DeepSeek-R1 and multi-token prediction

Qwen3 Coder vs Deepseek 0324: Benchmark

• Qwen3 Coder significantly outperforms DeepSeek 0324 in agentic coding tasks—including multi-turn reasoning, multilingual coding, and browser automation—making it an excellent choice for complex code agents and tool use scenarios.
• In general reasoning and knowledge benchmarks, DeepSeek 0324 holds a slight advantage, especially in MMLU-Pro and scientific reasoning (GPQA). However, Qwen3 Coder leads in most code generation tasks (especially HumanEval and LiveCodeBench).

Qwen3 Coder vs Deepseek 0324: Speed & Latency

Qwen3 Coder 480B-A35B consistently outperforms DeepSeek-V3 0324 in all measured speed and latency metrics: it generates output significantly faster, responds with lower latency, and delivers end-to-end results in less than half the time.

Qwen3 Coder vs Deepseek 0324: Using Cost

If you want to access locally:

Feature	Qwen3 Coder 480B A35B Instruct	DeepSeek V3 0324
GPU Model	H100	H100
GPUs Used	12 GPU	24 GPUs
Total Price	$30000 per GPU direct from NVIDIA	$30000 per GPU direct from NVIDIA
Cloud GPU Price (Novita AI)	$30.72/hr	$61.44/hr

If you want to use API like Novita AI:

Model	Context Window	Input Price (/1M tokens)	Output Price (/1M tokens)
Qwen3 Coder 480B A35B Instruct	262144	$2.00	$2.00
DeepSeek V3 0324	163840	$0.28	$1.14

Qwen3 Coder vs Deepseek 0324: Application

Qwen3 Coder

1. Simple and Straightforward Output, Focuses on Core Logic
   Qwen3 Coder likes to give you just what you need to get things running—no extra structure, just the essentials. Great for quick, no-frills coding tasks.
2. Fast Reasoning and Low Latency
   The model is optimized for speed, both in the cloud and locally. Perfect when you need to try things out fast or generate code frequently.
3. Strong Multilingual Coding, Easy to Port
   Trained on lots of languages, so it can handle Python, Java, C++, and more. The style is international and flexible.
4. Simple Structure, Beginner-Friendly
   Less abstraction and wrapping—variables and logic are clear and easy to follow. Great for teaching or learning.

Deepseek 0324

1. Well-Structured Output, Modular and Maintainable
   Deepseek focuses on best practices: clear function separation, comments, and error handling. The code is organized and easy to grow or maintain.
2. Detailed Comments and Reasoning, Team-Friendly
   Explains what it’s doing with comments and documentation. Makes it easy for teams to collaborate and understand the code.
3. Handles Complex Logic with Clear Reasoning
   Excels at breaking down tough business logic, algorithms, or scientific reasoning. You get clear, logical code step by step.
4. Engineering-Grade Structure, Easy to Integrate and Expand
   The code matches real-world engineering needs, so it’s ready for future updates and adding new modules.

Quick Comparison Table

Scenario/Feature	Qwen3 Coder	Deepseek 0324
Prototyping/Scripts	⭐⭐⭐⭐⭐	⭐⭐
Teaching/Examples	⭐⭐⭐⭐⭐	⭐⭐⭐
Large/Production Apps	⭐⭐	⭐⭐⭐⭐⭐
Detailed Comments/Docs	⭐⭐	⭐⭐⭐⭐⭐
Multilingual/Platforms	⭐⭐⭐⭐⭐	⭐⭐⭐
Maintainability/Scaling	⭐⭐	⭐⭐⭐⭐⭐

Qwen3 Coder is all about being simple, fast, and lightweight—perfect for small, quick, or teaching-oriented code.
Deepseek 0324 is structured, engineering-ready, well-documented, and great for big projects that need long-term maintenance and teamwork.

How to Access Qwen3 Coder and Deepseek 0324 via Novita API?

Step 1: Log In and Access the Model Library

Log in to your account and click on the Model Library button.

Step 2: Choose Your Model

Browse through the available options and select the model that suits your needs.

Step 3: Start Your Free Trial

Begin your free trial to explore the capabilities of the selected model.

Step 4: Get Your API Key

To authenticate with the API, we will provide you with a new API key. Entering the “Settings“ page, you can copy the API key as indicated in the image.

Step 5: Install the API

Install API using the package manager specific to your programming language.

After installation, import the necessary libraries into your development environment. Initialize the API with your API key to start interacting with Novita AI LLM. This is an example of using chat completions API for python users.

pip install 'openai>=1.0.0'
from openai import OpenAI
  
client = OpenAI(
    base_url="https://api.novita.ai/v3/openai",
    api_key="",
)

model = "qwen/qwen3-coder-480b-a35b-instruct"
stream = True # or False
max_tokens = 131072
system_content = ""Be a helpful assistant""
temperature = 1
top_p = 1
min_p = 0
top_k = 50
presence_penalty = 0
frequency_penalty = 0
repetition_penalty = 1
response_format = { "type": "text" }

chat_completion_res = client.chat.completions.create(
    model=model,
    messages=[
        {
            "role": "system",
            "content": system_content,
        },
        {
            "role": "user",
            "content": "Hi there!",
        }
    ],
    stream=stream,
    max_tokens=max_tokens,
    temperature=temperature,
    top_p=top_p,
    presence_penalty=presence_penalty,
    frequency_penalty=frequency_penalty,
    response_format=response_format,
    extra_body={
      "top_k": top_k,
      "repetition_penalty": repetition_penalty,
      "min_p": min_p
    }
  )

if stream:
    for chunk in chat_completion_res:
        print(chunk.choices[0].delta.content or "", end="")
else:
    print(chat_completion_res.choices[0].message.content)
  
  

Flexible Ways to Integrate: CLI, Agents, and Third-Party Platforms

Using CLI like Trae,Claude Code, Qwen Code

If you want to use Novita AI’s top models (like Qwen3-Coder, Kimi K2, DeepSeek R1) for AI coding assistance in your local environment or IDE, the process is simple: get your API Key, install the tool, configure environment variables, and start coding.

For detailed setup commands and examples, check the official tutorials:

• Trae : Step-by-Step Guide to Access AI Models in Your IDE
• Claude Code: How to Use Kimi-K2 in Claude Code on Windows, Mac, and Linux
• Qwen Code: How to Use OpenAI Compatible API in Qwen Code (60s Setup!)

Multi-Agent Workflows with OpenAI Agents SDK

Build advanced multi-agent systems by integrating Novita AI with the OpenAI Agents SDK:

• Plug-and-play: Use Novita AI’s LLMs in any OpenAI Agents workflow.
• Supports handoffs, routing, and tool use: Design agents that can delegate, triage, or run functions, all powered by Novita AI’s models.
• Python integration: Simply set the SDK endpoint to https://api.novita.ai/v3/openai and use your API key.

Connect Qwen 3 API on Third-Party Platforms

• Hugging Face: Use Qwen 3 in Spaces, pipelines, or with the Transformers library via Novita AI endpoints.
• Agent & Orchestration Frameworks: Easily connect Novita AI with platforms like Continue, AnythingLLM, LangChain, Dify, and Langflow through official connectors and integration guides.
• OpenAI-Compatible API: Enjoy seamless migration and integration with tools such as Cline and Cursor, designed for the OpenAI API standard.

Whether you’re building quick scripts, teaching code, or developing large-scale applications, both Qwen 3 Coder and Deepseek 0324 offer high-level AI coding support. Qwen 3 Coder is best for fast, lightweight, and beginner-friendly code, while Deepseek 0324 is ideal for complex, production-grade projects that demand clear structure and documentation. Thanks to Novita AI’s flexible API and integration options, you can easily test and switch between these models for different workflows—no matter your environment or platform.

Frequently Asked Questions

Novita AI is an AI cloud platform that offers developers an easy way to deploy AI models using our simple API, while also providing the affordable and reliable GPU cloud for building and scaling.

Recommended Reading

• Qwen3 Embedding 8B: Powerful Search, Flexible Customization, and Multilingual
• Qwen 3 in RAG Pipelines: All-in-One LLM, Embedding, and Reranking Models
• Kimi K2 vs GPT-4o: Which Best for AI Agent?