---
license: gemma
metrics:
- perplexity
base_model:
- google/gemma-3-1b-it-qat-q4_0-gguf
---
This is a requantized version of https://huggingface.co/google/gemma-3-1b-it-qat-q4_0-gguf.

The official QAT weights released by google use fp16 (instead of Q6_K) for the embeddings table, which makes this model take a significant extra amount of memory (and storage) compared to what Q4_0 quants are supposed to take. 
~~Instead of quantizing the table myself, I extracted it from Bartowski's quantized models, because those were already calibrated with imatrix, which should squeeze some extra performance out of it.~~
Requantizing with llama.cpp fixes that and gives better result than the other thing.

Here are some perplexity measurements:

| Model | File size ↓ | PPL (wiki.text.raw) ↓ |
| --- | --- | --- |
| [This model](https://huggingface.co/stduhpf/google-gemma-3-1b-it-qat-q4_0-gguf-small/blob/main/gemma-3-1b-it-q4_0_s.gguf) | 720 MB | 28.0468 +/- 0.26681 |
| [This model (older version)](https://huggingface.co/stduhpf/google-gemma-3-1b-it-qat-q4_0-gguf-small/blob/f325927302d106ad204c0b6a8f09f216a0447519/gemma-3-1b-it-q4_0_s.gguf) | 720 MB | 28.2603 +/- 0.26947 |
| [Q4_0 (bartowski)](https://huggingface.co/bartowski/google_gemma-3-1b-it-GGUF/blob/main/google_gemma-3-1b-it-Q4_0.gguf) | 722 MB | 34.4906 +/- 0.34539 |
| [QAT Q4_0 (google)](https://huggingface.co/google/gemma-3-1b-it-qat-q4_0-gguf/blob/main/gemma-3-1b-it-q4_0.gguf) | 1 GB | 28.0400 +/- 0.26669 |
| [BF16 (upscaled to f32 for faster inference)](https://huggingface.co/google/gemma-3-1b-it) | 2 GB | 29.1129 +/- 0.28170 |

Note that this model ends up smaller than the Q4_0 from Bartowski. This is because llama.cpp sets some tensors to Q4_1 when quantizing models to Q4_0 with imatrix, but this is a static quant.

I also fixed the control token metadata, which was slightly degrading the performance of the model in instruct mode. Shoutout to ngxson for [finding the issue](https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-gguf/discussions/3#67f6a2e0207b4bceea793151),
tdh111 for [making me aware of the issue](https://huggingface.co/stduhpf/google-gemma-3-27b-it-qat-q4_0-gguf-small/discussions/3#67f74fdf8411d4d6a82049db), 
and u/dampflokfreund on reddit ([Dampfinchen](https://huggingface.co/Dampfinchen) on Huggingface) for [sharing the steps to fix it](https://www.reddit.com/r/LocalLLaMA/comments/1jvi860/comment/mmcuvw2).
That model still struggles at long context with these fixes (just like the original qat model).