Google Gemma 3B Instruction-Tuned GGUF
| Property | Value |
|---|---|
| Original Model | google/gemma-3-27b-it |
| Quantization | GGUF format with imatrix |
| Size Range | 8.44GB - 54.03GB |
| Vision Support | Yes (requires MMPROJ file) |
What is google_gemma-3-27b-it-GGUF?
This is a comprehensive quantization suite of Google's Gemma 3B instruction-tuned model, optimized for various hardware configurations and use cases. The model features multiple compression levels using imatrix quantization, making it accessible for different computing environments while maintaining performance.
Implementation Details
The model utilizes llama.cpp's advanced quantization techniques, offering various compression options from Q8_0 (highest quality) to IQ2_XS (smallest size). Notable is its vision capability support through MMPROJ files, available in both F16 and F32 formats.
- Multiple quantization options ranging from 8.44GB to 54.03GB
- Vision capabilities through dedicated MMPROJ files
- Optimized for both CPU and GPU inference
- Support for online weight repacking on ARM and AVX systems
Core Capabilities
- Text generation and instruction following
- Vision-language processing (with MMPROJ)
- Flexible deployment options across different hardware
- Optimized performance through various quantization levels
Frequently Asked Questions
Q: What makes this model unique?
This implementation offers unprecedented flexibility in deployment through multiple quantization options, including new imatrix quantization techniques that provide better performance-to-size ratios. It also includes vision capabilities, making it a versatile choice for multimodal applications.
Q: What are the recommended use cases?
For most users, the Q4_K_M variant (16.55GB) offers a good balance of quality and size. Users with limited RAM should consider IQ3/IQ2 variants, while those prioritizing quality should opt for Q6_K_L or higher quantization levels. The model supports both text-only and vision-language tasks when properly configured.
