32B Parameter AI Models Compared Best for Businesses and Professionals

32B Parameter AI Models Compared Best for Businesses and Professionals

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AI Summary

Video Summary: Comparison of 32 Billion Parameter AI Models

This video compares popular AI models of 32 billion parameters, focusing on cost-effectiveness and performance for business applications. The models discussed include:

• Deep Sea R1 Distilled
• Skyworks O1
• GLM Rumination Co 32 Billion
• Quen 2.5 VL
• QWQ

Key Comparison Points:

1. Models Overview:
   • Provides quick specs on parameter count, architecture (e.g., vision transformers), training techniques, context windows, and licensing (preferable licenses include Apache 2).
2. Reasoning and Coding Capabilities:
   • Highlights models with strong reasoning skills:
     • Deep Sea R1 Distilled and Skyworks O1 excel in math and coding.
     • GLM Rumination adds multi-step reasoning and complex task-solving capabilities.
     • Quen 2.5 VL is better for vision-related challenges.
3. Training and Optimization:
   • Discusses the use of reinforcement learning (RL) and techniques for enhancing model outputs:
     • Notable RL approaches include multi-stage RL for improved reasoning (Deep Sea R1) and efficient training through customized systems (Skyworks O1).
4. Deployment and Openness:
   • All models can run locally on well-equipped hardware.
   • Skyworks O1 is noted for its openness, with code and datasets available.
5. Use Cases:
   • Recommendations for different tasks:
     • Math-heavy tasks: Skyworks or Deep Sea R1.
     • Programming: GLM, Skyworks, or Deep Sea R1.
     • Document parsing and vision tasks: Quen 2.5 VL.
     • Complex research tasks: GLM or QWQ.

Conclusion:
The landscape of AI models is rapidly evolving, and this comparison reflects the status at the time of recording. The video encourages viewers to seek further details of each model on the channel and to share experiences with other models in the comments.