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About the Provider

Qwen is an AI model family developed by Alibaba Group, a major Chinese technology and cloud computing company. Through its Qwen initiative, Alibaba builds and open-sources advanced language, images and coding models under permissive licenses to support innovation, developer tooling, and scalable AI integration across applications.

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Model Quickstart

This section helps you quickly get started with the Qwen/Qwen3-Coder-Plus model on the Qubrid AI inferencing platform. To use this model, you need:
  • A valid Qubrid API key
  • Access to the Qubrid inference API
  • Basic knowledge of making API requests in your preferred language
Once authenticated with your API key, you can send inference requests to the Qwen/Qwen3-Coder-Plus model and receive responses based on your input prompts. Below are example placeholders showing how the model can be accessed using different programming environments.
You can choose the one that best fits your workflow. 
from openai import OpenAI

# Initialize the OpenAI client with Qubrid base URL
client = OpenAI(
    base_url="https://platform.qubrid.com/v1",
    api_key="QUBRID_API_KEY",
)

# Create a streaming chat completion
stream = client.chat.completions.create(
    model="Qwen/Qwen3-Coder-Plus",
    messages=[
      {
        "role": "user",
        "content": "Write a Python function to calculate fibonacci sequence"
      }
    ],
    max_tokens=8962,
    temperature=0.1,
    top_p=1,
    stream=True
)

# If stream = False comment this out
for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)
print("\n")

# If stream = True comment this out
print(stream.choices[0].message.content)

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Model Overview

Qwen3 Coder Plus is a powerful Coding Agent built on Qwen3 that excels in tool calling and environment interaction to achieve autonomous programming.
  • It combines outstanding coding proficiency with versatile general-purpose abilities.
  • With a Transformer decoder-only architecture and up to 1M token context length, it is designed for code generation, debugging, refactoring, and API design workflows.

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Model at a Glance

FeatureDetails
Model IDQwen/Qwen3-Coder-Plus
ProviderAlibaba Cloud (Qwen Team)
ArchitectureTransformer decoder-only
Model SizeN/A
Parameters4
Context LengthUp to 1M Tokens
Release Date2025
LicenseApache 2.0
Training DataCode-focused datasets with instruction tuning

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When to use?

You should consider using Qwen3 Coder Plus if:
  • You need code generation across multiple languages
  • Your application requires debugging and refactoring workflows
  • You are building autonomous coding agents with tool calling
  • Your use case involves API design and full-stack development
  • You need long-context support for large codebases

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Inference Parameters

Parameter NameTypeDefaultDescription
StreamingbooleantrueEnable streaming responses for real-time output.
Temperaturenumber0.1Lower temperature for more deterministic code generation.
Max Tokensnumber8962Maximum number of tokens the model can generate.
Top Pnumber1Controls nucleus sampling for more predictable output.

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Key Features

  • Autonomous Coding Agent: Excels in tool calling and environment interaction to achieve end-to-end autonomous programming.
  • Outstanding Coding Proficiency: Strong performance across code generation, debugging, refactoring, and API design.
  • Up to 1M Token Context: Supports very long codebases and complex multi-file reasoning workflows.
  • Versatile General-Purpose Abilities: Combines coding strength with broad language understanding for mixed workflows.

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Summary

Qwen3 Coder Plus is Alibaba’s powerful open-source coding agent built for autonomous programming workflows.
  • It uses a Transformer decoder-only architecture with up to 1M token context and instruction tuning on code-focused datasets.
  • It excels in tool calling, environment interaction, code generation, debugging, and API design.
  • The model supports long-context coding workflows and versatile general-purpose tasks.
  • Licensed under Apache 2.0 for full commercial use.