Google Gemma 3 Beats DeepSeek V3 100% FREE and Local!

Google Gemma 3 Beats DeepSeek V3 100% FREE and Local!

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AI Summary

Summary of Jemma 3 Video

• Introduction:
  • Jemma 3 is a highly capable model for single GPU or TPU operation.
  • Outperforms Llama 45 billion parameter model in human preference evaluations.
  • Supports 140 languages out of the box, focusing on 35 languages.
  • Capable of analyzing image text and short videos with a 128,000 token context window.
  • Function calling supports agent creation, even with quantized models.
• Comparison:
  • Jemma 3 (27 billion parameters) outperforms Deep Seek V3 (671 billion parameters) and is close to Deep Seek R1.
  • Ranked in top 10 on LM Arena, surpassing models like Quen 2.5 Max.
• Versions Available:
  • Released in four versions: 27B, 12B, 4B, and 1B parameters.
  • It is multimodal and memory efficient.
  • Available for testing on Hugging Face and Google AI Studio via API.
• Setup Instructions:
  1. Install main package:

     pip install ol  

  2. Download Olama using:

     ol pull Jama 3  

  3. Create a simple application in Python to interact with Jemma 3.
  4. Create a UI using Chainlit and run the chatbot locally.
• Creating AI Agents:
  • Use pip install praon to install agent functionalities.
  • Simple commands allow for setting up agents that can automate tasks like generating LinkedIn posts and tweets.
  • Example code demonstrates the creation of two agents working collaboratively.
• Conclusion:
  • Jemma 3 runs completely locally, maintaining data privacy.
  • Allows users to create multiple agents for various tasks.
  • Overall impression is positive; Jemma 3 is highlighted as a free and effective model for language processing tasks.