Qwen3-Coder-480B-A35B-Instruct

Description

Qwen3-Coder-480B-A35B-Instruct is an advanced AI model developed to enhance agentic coding tasks. It is part of the Qwen series and represents the most powerful variant available. The model is designed to perform exceptionally well in agentic coding and browser-use tasks, achieving results comparable to other leading models like Claude Sonnet.

One of the standout features of Qwen3-Coder-480B-A35B-Instruct is its long-context capabilities. It natively supports 256K tokens, which can be extended up to 1 million tokens using Yarn, making it optimized for repository-scale understanding. This allows users to handle large-scale coding projects with ease.

The model is built with a causal language model architecture, featuring 480 billion parameters in total, with 35 billion activated. It includes 62 layers and 96 attention heads for query and 8 for key-value pairs. Additionally, it has 160 experts, with 8 activated, providing robust performance in various coding tasks.

Qwen3-Coder-480B-A35B-Instruct supports agentic coding for most platforms, including Qwen Code and CLINE, and features a specially designed function call format. It is recommended to use the latest version of transformers for optimal performance, as older versions may encounter errors.

For local use, applications such as Ollama, LMStudio, MLX-LM, llama.cpp, and KTransformers support Qwen3. Users are advised to configure sampling parameters for best results, including temperature, top_p, top_k, and repetition penalty settings. The model is suitable for developers and researchers looking for a high-performance coding AI tool.

Qwen3-Coder-480B-A35B-Instruct Highlights

• Agentic coding performance

• Long-context capabilities

• Causal language model architecture

• 480 billion parameters

• 256K native token support

• Tool calling capabilities

• Special function call format

• Optimized for repository-scale understanding

• Supports Qwen Code and CLINE

• Recommended transformers version

Getting Started with Qwen3-Coder-480B-A35B-Instruct

1. 1

   Access page: Visit the Hugging Face model page

2. 2

   Load model: Download and initialize Qwen3-Coder

3. 3

   Configure environment: Set sampling parameters

4. 4

   Integrate: Use with supported applications

5. 5

   Fine-tune: Adjust model settings for specific tasks

Qwen3-Coder-480B-A35B-Instruct's Use Cases

• Agentic coding
• Long-context projects
• Tool integration
• Repository understanding
• Function call design

FAQ from Qwen3-Coder-480B-A35B-Instruct

• What is Qwen3-Coder-480B-A35B-Instruct?

  It is a powerful AI model designed for agentic coding tasks with long-context capabilities.

• What are the key features of Qwen3-Coder-480B-A35B-Instruct?

  Key features include agentic coding performance, long-context support, and tool calling capabilities.

• How many parameters does Qwen3-Coder-480B-A35B-Instruct have?

  The model has 480 billion parameters in total, with 35 billion activated.

• What is the context length supported by Qwen3-Coder-480B-A35B-Instruct?

  It supports 256K tokens natively, extendable up to 1 million tokens using Yarn.

• Which platforms support Qwen3-Coder-480B-A35B-Instruct?

  It supports platforms like Qwen Code and CLINE.

• What sampling parameters are recommended for Qwen3-Coder-480B-A35B-Instruct?

  Recommended parameters include temperature=0.7, top_p=0.8, top_k=20, and repetition_penalty=1.05.

• What applications support local use of Qwen3-Coder-480B-A35B-Instruct?

  Applications like Ollama, LMStudio, MLX-LM, llama.cpp, and KTransformers support local use.

• What should I do if I encounter out-of-memory issues?

  Consider reducing the context length to a shorter value, such as 32,768 tokens.