Gemma3 versus its peers: Gemma3 vs Phi4 vs Mistral NeMo

Small Language Models (SLM) are advancing quickly to make generative AI more accessible and affordable. With SLMs you can run powerful AI models on traditional CPUs and low RAM. In this comparison, we look at the best three SLMs out there:

• Google’s Gemma3 (12b)

• Microsoft’s Phi-4 (14b)

• Mistral’s NeMo (12b)

Each of these models has its strengths and weaknesses. In this blog, we’ll take a look at:

• How they’re built and trained

• How much text they can handle at once

• How well they perform in different tasks

• How Affordable Are They to Use
  

Choosing the right model can be tricky, but by the end of this blog, you'll know which one fits your needs best. Let’s dive into what makes each model unique and how they stack up against each other.

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Overview of the Models

1. Google Gemma3 (12b)

• Based on Google’s Gemini technology

• Can process both text and images

• Supports very long documents (128K tokens)

• Uses smart attention techniques to process text efficiently

• Available in 1b, 4b, 12b, and 27b sizes
  

2. Microsoft Phi-4 (14b)

• Trained on high-quality educational and internet data

• Designed to think logically and solve math problems

• Handles up to 16K tokens at a time

• License restrictions apply for business use
  

3. Mistral NeMo (12b)

• Created with help from NVIDIA for fast performance

• Supports very long documents (128K tokens)

• Works well with multiple languages

• Uses an advanced tokenizer to compress non-English text better

• Open-source license allows free commercial use

  
  

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Comparison Factors

1.

Comparison of maximum token processing capabilities for three AI models: Gemma 3 and Mistral AI both support up to 128K tokens, while Phi-4 supports 16K tokens.

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2.

Benchmark performance comparison of three AI models, Gemma 3, Phi-4, and Mistral AI, on HellaSwag (10-shot) and MMLU (5-shot) tasks, highlighting Phi-4's leading results with scores of 85.6 and 80.3, respectively.

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3.

Overview of primary use cases for AI models: Gemma 3 excels in text and image processing, Phi-4 is ideal for logic and math tasks, and Mistral AI is best suited for handling multi-language and long documents.

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4.

Comparison of Memory Requirements for AI Models: Gemma 3 (8.1GB), Microsoft Phi-4 (9.1GB), and Mistral AI (7.1GB) showcasing affordability.

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Conclusion

Here’s a quick summary of which model is best for what:

• Gemma3 is perfect for projects that mix text and images.

• Phi-4 is ideal if you need to work on tasks with math or logic.

• Mistral NeMo is the best choice if you're dealing with long texts or multilingual content.

If you need a model with no restrictions for business use, Mistral NeMo is your best option. 

If you’re working on math or logic-heavy tasks, Phi-4 is the way to go. 

For creative projects that require text and image processing, Gemma3 is the best fit.