Gemma 3 - NEW Opensource Multimodal Model Beats DeepSeek V3 & o3 Mini! (Fully Tested)

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AI Summary

Summary of Google’s Gamma 3 AI Model Introduction

• Introduction of Gamma 3:
  • Google released Gamma 3, a collection of lightweight, state-of-the-art open AI models.
  • Built on the same technology as Google’s Gemini 2.0.
  • Designed for efficiency with four models: 1B, 4B, 12B, and 27B parameters.
  • Pre-trained in over 140 languages with native support for 35+ languages.
  • Open-based models, installable locally with Llama or LM Studio.
  • Multimodal capabilities (excluding the 1B model) for text, images, and short videos.
  • Supports up to 128k tokens (1B model supports 32k tokens).
  • Outperforms larger models like Deep Seek v3 and Llama 3 in benchmarks.
• Performance and Deployment:
  • Significant improvement over the previous model, Gamma 2, in benchmarks.
  • Can be deployed on phones, web, or cloud.
  • Installation instructions provided for accessing endpoints via Hugging Face or using AMA.
  • LM Studio allows for easy installation and access within their chat interface.
  • Google’s AI Studio offers a free web interface for interacting with Gamma 3 models.
• Model Assessment with Prompts:
  • Successfully generated a detailed web app for tracking finances using HTML, CSS, and JavaScript.
  • Created a short story based on images, demonstrating image understanding and object recognition.
  • Failed to generate accurate SVG code for a symmetrical butterfly.
  • Solved a simple algebra equation correctly.
  • Demonstrated logical reasoning by calculating the total milk production from cows and goats over a week.
  • Correctly debugged a Python function to sum even numbers in a list.
  • Showed common sense reasoning by explaining what happens to water in freezing temperatures.
• Conclusion:
  • Gamma 3 is a versatile model that performs well in math, multimodal tasks, and general knowledge.
  • It is accessible for local deployment and can be run on a single GPU or CPU.
  • While it has limitations in coding tasks, it excels in other areas and is open for consumer use.

Detailed Instructions and URLs (if provided in the transcript)

• Installation and Access:
  • No specific CLI commands or URLs were provided in the summary.
  • General reference to Hugging Face and LM Studio for model access.
  • Mention of Google’s AI Studio for web interaction with the model.

Notes

• The summary excludes any self-promotion, subscription requests, or social media mentions from the author.
• No URLs or specific commands were included in the provided summary, indicating they were not present in the transcript.