---
license: gemma
library_name: transformers
pipeline_tag: image-text-to-text
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: To access Gemma on Hugging Face, you’re required to review and
  agree to Google’s usage license. To do this, please ensure you’re logged in to Hugging
  Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
base_model: google/gemma-3-12b-it
tags:
- TensorBlock
- GGUF
---

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## google/gemma-3-12b-it - GGUF

This repo contains GGUF format model files for [google/gemma-3-12b-it](https://huggingface.co/google/gemma-3-12b-it).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4882](https://github.com/ggml-org/llama.cpp/commit/be7c3034108473beda214fd1d7c98fd6a7a3bdf5).

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## Prompt template

```
<bos><start_of_turn>user
{system_prompt}

{prompt}<end_of_turn>
<start_of_turn>model
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [gemma-3-12b-it-Q2_K.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q2_K.gguf) | Q2_K | 4.768 GB | smallest, significant quality loss - not recommended for most purposes |
| [gemma-3-12b-it-Q3_K_S.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q3_K_S.gguf) | Q3_K_S | 5.458 GB | very small, high quality loss |
| [gemma-3-12b-it-Q3_K_M.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q3_K_M.gguf) | Q3_K_M | 6.009 GB | very small, high quality loss |
| [gemma-3-12b-it-Q3_K_L.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q3_K_L.gguf) | Q3_K_L | 6.480 GB | small, substantial quality loss |
| [gemma-3-12b-it-Q4_0.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q4_0.gguf) | Q4_0 | 6.887 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [gemma-3-12b-it-Q4_K_S.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q4_K_S.gguf) | Q4_K_S | 6.935 GB | small, greater quality loss |
| [gemma-3-12b-it-Q4_K_M.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q4_K_M.gguf) | Q4_K_M | 7.301 GB | medium, balanced quality - recommended |
| [gemma-3-12b-it-Q5_0.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q5_0.gguf) | Q5_0 | 8.232 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [gemma-3-12b-it-Q5_K_S.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q5_K_S.gguf) | Q5_K_S | 8.232 GB | large, low quality loss - recommended |
| [gemma-3-12b-it-Q5_K_M.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q5_K_M.gguf) | Q5_K_M | 8.445 GB | large, very low quality loss - recommended |
| [gemma-3-12b-it-Q6_K.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q6_K.gguf) | Q6_K | 9.661 GB | very large, extremely low quality loss |
| [gemma-3-12b-it-Q8_0.gguf](https://huggingface.co/tensorblock/gemma-3-12b-it-GGUF/blob/main/gemma-3-12b-it-Q8_0.gguf) | Q8_0 | 12.510 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/gemma-3-12b-it-GGUF --include "gemma-3-12b-it-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/gemma-3-12b-it-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```