Gemma 3 (Fully Tested) : This NEW Google MODEL Beats Deepseek? IT MIGHT BE A LOCAL Gemini FLASH!

Gemma 3 Model Review: Capabilities and Limitations

Key Concepts:

• Gemma 3: Google's new open-source model lineup.
• Model Sizes: 1B, 4B, 12B, and 27B parameters.
• Multimodal: Ability to process different types of data (text, images, potentially video).
• Function Calling: Ability to interact with external tools and APIs.
• LMSYS Arena: A leaderboard for evaluating language models based on human preference.
• Quantization: A technique to reduce the size and computational cost of a model.
• Dart AI: An AI-powered product management tool.

1. Introduction to Gemma 3

• Google has launched Gemma 3, its new open-source model lineup, built on the same research and technology as Gemini 2.0.
• Gemma 3 is designed to be capable of running on a single GPU or TPU.
• The model comes in various sizes: 1B, 4B, 12B, and 27B parameters.
• The 27B model is claimed to outperform Llama 45B, DeepSeek V3, and Qwen 1.5 03 Mini in preliminary human preference evaluations on the LMSYS Arena leaderboard.
• It supports 140 languages and is multimodal, supporting function calling.
• A quantized version is also available.

2. Availability and Access

• Gemma 3 is available for trial on AI Studio.
• It can be used locally via AMA (likely referring to a local inference setup).

3. Quick Dart AI Advertisement

• Dart AI is introduced as an AI-powered product management tool.
• Features include:
  • Generating project plans from prompts.
  • Detecting duplicate tasks.
  • Creating subtasks.
  • Assigning tasks to AI for completion.
  • Generating blog posts, research topics, and thumbnails.
• Dart AI is free for teams up to four people, with paid plans available for larger teams.
• Integrations include GitHub, Slack, Discord, and an API for custom workflows.

4. Testing Methodology

• The video tests Gemma 3 against 13 questions to evaluate its capabilities.
• The questions cover various areas, including:
  • General knowledge.
  • Rhyming and wordplay.
  • Creative writing (Haiku).
  • Latin adjective identification.
  • Pattern recognition.
  • Mathematical reasoning.
  • Logical reasoning.
  • HTML, CSS, and JavaScript code generation.
  • SVG code generation.
  • Python programming (game of life, bouncing ball simulation).

5. Test Results and Analysis

• Successful Tests (Pass):
  • Identifying a country ending in "lia" and its capital (Australia and Canberra).
  • Identifying the number that rhymes with "tree" (three).
  • Solving the "apples" word problem (two apples left).
  • Solving the "Sally and her brothers" word problem.
  • Calculating the long diagonal of a hexagon given the short diagonal.
  • Generating HTML/CSS/JS code for a button that explodes confetti.
  • Generating a working game of life in Python for the terminal.
• Failed Tests (Fail):
  • Writing a haiku where the second letter of each word spells "simple."
  • Naming an English adjective of Latin origin with specific letter constraints (transparent).
  • Solving the pattern recognition question.
  • Creating a playable synth keyboard using HTML/CSS/JS.
  • Generating SVG code for a butterfly.
  • Writing a Python program that shows a ball bouncing inside a spinning hexagon.

6. Overall Assessment

• The model is considered "fine" but not "extremely good."
• It is usable, especially for multiple language support.
• Coding aspects are considered "bad," similar to Gemini models.
• The model is in a "limbo situation" where it's good, but better options are available depending on the use case.
• The multimodal capability is a significant advantage, setting it apart from other models of similar size.
• The model supports short videos, which is "awesome to see" for an open-source model.
• The reviewer speculates that it might be a pruned-down version of a previous generation Flash model.
• The 4B model is also considered "cool" due to its multimodality.
• It is available via a free API.

7. Key Strengths and Weaknesses

• Strengths:
  • Multilingual support (140 languages).
  • Multimodal capabilities (text, images, potentially video).
  • Function calling.
  • Availability via free API.
• Weaknesses:
  • Poor coding performance.
  • Inconsistent performance across different tasks.

8. Conclusion

Gemma 3 is a usable open-source model with notable strengths in multilingual support and multimodality. However, its coding capabilities are limited, and its overall performance is inconsistent. The model's multimodality and availability via a free API make it a potentially valuable tool for specific use cases, particularly those involving multiple languages or multimodal data. The reviewer suggests that the 4B model is particularly interesting due to its multimodal capabilities.