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What is Qwen3-Coder?

Qwen3-Coder is a multifaceted coding model available in different sizes, prominently showcasing the 480B-parameter Mixture-of-Experts variant with 35B active parameters, which adeptly manages 256K-token contexts that can be scaled up to 1 million tokens. It demonstrates remarkable performance comparable to Claude Sonnet 4, having been pre-trained on a staggering 7.5 trillion tokens, with 70% of that data comprising code, and it employs synthetic data fine-tuned through Qwen2.5-Coder to bolster both coding proficiency and overall effectiveness. Additionally, the model utilizes advanced post-training techniques that incorporate substantial, execution-guided reinforcement learning, enabling it to generate a wide array of test cases across 20,000 parallel environments, thus excelling in multi-turn software engineering tasks like SWE-Bench Verified without requiring test-time scaling. Beyond the model itself, the open-source Qwen Code CLI, inspired by Gemini Code, equips users to implement Qwen3-Coder within dynamic workflows by utilizing customized prompts and function calling protocols while ensuring seamless integration with Node.js, OpenAI SDKs, and environment variables. This robust ecosystem not only aids developers in enhancing their coding projects efficiently but also fosters innovation by providing tools that adapt to various programming needs. Ultimately, Qwen3-Coder stands out as a powerful resource for developers seeking to improve their software development processes.

What is DeepSeek-Coder-V2?

DeepSeek-Coder-V2 represents an innovative open-source model specifically designed to excel in programming and mathematical reasoning challenges. With its advanced Mixture-of-Experts (MoE) architecture, it features an impressive total of 236 billion parameters, activating 21 billion per token, which greatly enhances its processing efficiency and overall effectiveness. The model has been trained on an extensive dataset containing 6 trillion tokens, significantly boosting its capabilities in both coding generation and solving mathematical problems. Supporting more than 300 programming languages, DeepSeek-Coder-V2 has emerged as a leader in performance across various benchmarks, consistently surpassing other models in the field. It is available in multiple variants, including DeepSeek-Coder-V2-Instruct, tailored for tasks based on instructions, and DeepSeek-Coder-V2-Base, which serves well for general text generation purposes. Moreover, lightweight options like DeepSeek-Coder-V2-Lite-Base and DeepSeek-Coder-V2-Lite-Instruct are specifically designed for environments that demand reduced computational resources. This range of offerings allows developers to choose the model that best fits their unique requirements, ultimately establishing DeepSeek-Coder-V2 as a highly adaptable tool in the ever-evolving programming ecosystem. As technology advances, its role in streamlining coding processes is likely to become even more significant.

Media

Media

Integrations Supported

Gemini
Nebius Token Factory
Okara
OpenCode
Oxlo.ai
SiliconFlow
Tinfoil
Together AI

Integrations Supported

C
C#
C++
Clojure
Elixir
Go
HTML
JavaScript
Julia
Ruby
SQL
Visual Basic

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Qwen

Date Founded

2023

Company Location

China

Company Website

qwenlm.github.io/blog/qwen3-coder/

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

www.deepseek.com

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Categories and Features

AI Code Generators

Not specified

AI Coding Models

Not specified

AI Models

Not specified

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