---
license: gemma
base_model: google/gemma-3-4b-it
pipeline_tag: text-generation
library_name: rkllm
tags:
- rkllm
- rockchip
- rk3576
- rk3588
- gemma
- gemma-3
---

# gemma-3-4b-it · RKLLM

Text generation on Rockchip RK3576 and RK3588, converted from [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it).

**The files currently published here are text-only.** The source model supports images, but this conversion does not include a vision encoder.

- **Conversion toolkit:** RKLLM Toolkit 1.2.3.
- **Inputs / output:** text → text.
- **License:** `gemma`; the [upstream model card](https://huggingface.co/google/gemma-3-4b-it) describes its terms and intended use.

## Choose your files

Use the files for your board’s exact SoC. `w4a16` uses 4-bit weights and 16-bit activations; `w4a16_g128` adds a weight group size of 128. `w8a8` uses 8-bit weights and activations. File size below is download size, not total runtime RAM.

| Board | Quantization | Size | Language model |
| --- | --- | --- | --- |
| RK3576 | `w4a16` | 3.42 GiB | [gemma-3-4b-it_RK3576_w4a16.rkllm](RK3576/gemma-3-4b-it_RK3576_w4a16.rkllm) |
| RK3576 | `w8a8` | 4.92 GiB | [gemma-3-4b-it_RK3576_w8a8.rkllm](RK3576/gemma-3-4b-it_RK3576_w8a8.rkllm) |
| RK3588 | `w8a8` | 4.90 GiB | [gemma-3-4b-it_RK3588_w8a8.rkllm](RK3588/gemma-3-4b-it_RK3588_w8a8.rkllm) |

## Run on your board

With Docker installed on a matching Rockchip board, this example starts the **RK3576 w4a16** model and its API on port 8001:

```bash
sudo docker run --rm -d --name rkllm \
  --privileged -v /dev:/dev -p 8001:8001 \
  ghcr.io/hanzo-huang/rkllm-docker/llm/gemma-3-4b-it:rk3576-w4a16
```

The image includes its model file. See [rkllm-docker](https://github.com/Hanzo-Huang/rkllm-docker#readme) for API requests, other board variants, and configuration.

To download the files separately instead:

```bash
hf download HanzoHuang/gemma-3-4b-it-RKLLM \
  RK3576/gemma-3-4b-it_RK3576_w4a16.rkllm \
  --local-dir ./models
```

These are native RKLLM/RKNN artifacts. Use a compatible RKLLM runtime and the model’s correct chat template when integrating them in another application.

## Release notes

No per-variant board benchmark is published here. Quantized output may differ from the original model; check responses on your own workloads. Use the toolkit version listed above when checking runtime compatibility.

<details>
<summary>SHA-256 checksums</summary>

```text
0e6d6298453f483e832a7982bcdf1acdf895a47c6777e93eb3c1e43e82cf8fc2  RK3576/gemma-3-4b-it_RK3576_w4a16.rkllm
b077e9ee75f837230dbf1be948a03d39942abd90ab23343399fa13b7d19526cf  RK3576/gemma-3-4b-it_RK3576_w8a8.rkllm
aa04fce6ca2e418cd946814f1563fe8ed7e56dfbf5cf99ced4e753739287ee80  RK3588/gemma-3-4b-it_RK3588_w8a8.rkllm
```

</details>

## Credits

Original model: [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it). Conversion tools: [Rockchip RKLLM](https://github.com/airockchip/rknn-llm).