Gemma-3 4B GGUF
| Property | Value |
|---|---|
| Model Size | 4B parameters |
| Context Window | 128K tokens |
| Author | Google DeepMind (Base model), Unsloth (GGUF version) |
| Technical Report | Gemma 3 Technical Report |
What is gemma-3-4b-it-GGUF?
Gemma-3 4B GGUF is an optimized version of Google's Gemma language model, converted to the efficient GGUF format by Unsloth. It represents a lightweight yet powerful multimodal AI model capable of processing both text and images while generating text outputs. Built using the same technology behind Google's Gemini models, it offers state-of-the-art performance in a compact form factor.
Implementation Details
The model was trained using TPU hardware (TPUv4p, TPUv5p, and TPUv5e) with JAX and ML Pathways frameworks. This 4B parameter version was trained on approximately 4 trillion tokens, encompassing web documents, code, mathematics, and image data.
- Supports input context of 128K tokens
- Handles images at 896x896 resolution
- Processes over 140 languages
- Optimized for efficient deployment on consumer hardware
Core Capabilities
- Multimodal processing (text and image inputs)
- Strong performance on reasoning tasks (77.2% on HellaSwag)
- Code generation capabilities (36.0% on HumanEval)
- Effective multilingual support (68.0% on XQuAD)
- Image understanding (72.8% on DocVQA)
Frequently Asked Questions
Q: What makes this model unique?
The model combines Google's advanced AI technology with Unsloth's optimization for efficient deployment. It offers an impressive balance of performance and resource requirements, making it accessible for deployment on consumer hardware while maintaining strong capabilities across multiple tasks.
Q: What are the recommended use cases?
The model excels in content creation, chatbot applications, text summarization, and image data extraction. It's particularly well-suited for research and educational applications, including NLP research, language learning tools, and knowledge exploration tasks.
