GLM-4 32B (+ Free APIs) + RooCode & Cline I’m BLOWN AWAY by this INSANE Model (Beat 32B Coder!)
AI Summary
Summary of the GLM 432B Model Review
- Introduction
- Discussion begins with a review of the GLM 432B model, which is highlighted as an impressive coding model.
- Model Overview
- Developed by Thudm (Tsinghua University and Zai).
- Part of the GLM 4 series, which includes multiple models tailored for coding tasks.
- GLM 432B is specifically noted for exceptional performance in coding tasks.
- Compared favorably against other models like Gemini 2.5, while having some limitations.
- Performance Highlights
- First 32B model to successfully pass all five coding questions with promising results.
- Effective at handling specific coding tasks, though not suitable for general usage.
- Achieves good results for simple HTML and Python applications.
- Technical Requirements
- Can be run on a MacBook with 32 GB of RAM or an RTX 490.
- Weights available on Hugging Face and LLaMA, with APIs also accessible.
- Affordable API options available (e.g., Novita: $0.24 per million tokens).
- Usage Recommendations
- Best experienced through R code, which shows stronger performance.
- Tips on setting up the API and using a Next.js app for tasks like building an image cropper tool.
- Notable that the model may glitch or confuse certain setups due to training data limitations.
- Offers a fascinating feature of “self-talk” during code generation.
- Conclusion
- Overall, GLM 432B presents an effective tool for local coding tasks with great potential for further fine-tuning.