Qwen 2.5 Coder 32B: Is This Best Open Weight Model Better than GPT-4o?


Summary

The video introduces the Quin 2.5 model and its variations up to 32 billion, showcasing its performance compared to other models like GBD40 and CL 3.5 in benchmarks. It demonstrates how to build code-based applications with Quin for edge devices ranging from half a billion to 32 billion. The discussion covers leaderboards, including the Quin quarter model and CL 3.5 HIU model, as well as creating web applications like a snake game in Python and generating images using an external API. The step-by-step explanation of implementation processes for backend and API servers, as well as JavaScript interaction, is detailed, along with successful local testing.


Introduction to Quin 2.5 Model

Introduction to the new Quin 2.5 model and its different versions up to 32 billion, highlighting its performance compared to other models like GBD40 and CL 3.5 in benchmarks.

Building Code-Based Applications

Demonstration of how to build code-based applications using the Quin model, specifically focusing on sizes ranging from half a billion to 32 billion for edge devices.

Exploring Leaderboards and Code Refactoring

Discussion on different types of leaderboards, including code refactoring leaderboard and small coding access sizes. Mention of the Quin quarter model and CL 3.5 HIU model in the context of leaderboards.

Creating Web Applications

Creating simple web applications, like a snake game in Python, by experimenting with HTML code and animations, and testing them on two different applications.

Generating Images Using External API

Demonstration of creating a web application to generate images using an external API, involving text input from the user and displaying the generated image on the web page.

Implementation and Testing

Explanation of the implementation process using a detailed prompt to generate code for a backend server, API server, and JavaScript interaction. Testing the generated code locally with successful outcomes.

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