> This page is for version v1.1.0.
> For other versions, use one of these documentation indexes:
> - Latest (v1.5.1) (default): https://docs.nvidia.com/dynamo/latest/llms.txt
> - dev: https://docs.nvidia.com/dynamo/dev/llms.txt
> - v1.5.1: https://docs.nvidia.com/dynamo/v1.5.1/llms.txt
> - v1.5.0: https://docs.nvidia.com/dynamo/v1.5.0/llms.txt
> - v1.4.2: https://docs.nvidia.com/dynamo/v1.4.2/llms.txt
> - v1.4.1: https://docs.nvidia.com/dynamo/v1.4.1/llms.txt
> - v1.4.0: https://docs.nvidia.com/dynamo/v1.4.0/llms.txt
> - v1.3.0: https://docs.nvidia.com/dynamo/v1.3.0/llms.txt
> - v1.2.1: https://docs.nvidia.com/dynamo/v1.2.1/llms.txt
> - v1.2.0: https://docs.nvidia.com/dynamo/v1.2.0/llms.txt
> - v1.1.1: https://docs.nvidia.com/dynamo/v1.1.1/llms.txt
> - v1.1.0: https://docs.nvidia.com/dynamo/v1.1.0/llms.txt
> - v1.0.2: https://docs.nvidia.com/dynamo/v1.0.2/llms.txt
> - v1.0.1: https://docs.nvidia.com/dynamo/v1.0.1/llms.txt
> - v1.0.0: https://docs.nvidia.com/dynamo/v1.0.0/llms.txt
> - v0.9.1: https://docs.nvidia.com/dynamo/v-0-9-1/llms.txt
> - v0.9.0: https://docs.nvidia.com/dynamo/v-0-9-0/llms.txt
> - v0.8.1: https://docs.nvidia.com/dynamo/v-0-8-1/llms.txt
> - v0.8.0: https://docs.nvidia.com/dynamo/v-0-8-0/llms.txt
> - v0.7.1: https://docs.nvidia.com/dynamo/v-0-7-1/llms.txt
> - v0.7.0: https://docs.nvidia.com/dynamo/v-0-7-0/llms.txt

> For clean Markdown content of this page, append .md to this URL. For the complete documentation index, see https://docs.nvidia.com/dynamo/llms.txt. For full content including API reference and SDK examples, see https://docs.nvidia.com/dynamo/llms-full.txt.

# Gemma3 Sliding Window

For general TensorRT-LLM features and configuration, see the [Reference Guide](/dynamo/v1.1.0/backends/tensor-rt-llm/reference-guide).

---

This guide demonstrates how to deploy google/gemma-3-1b-it with Variable Sliding Window Attention (VSWA) using Dynamo. Since google/gemma-3-1b-it is a small model, each aggregated, decode, or prefill worker only requires one H100 GPU or one GB200 GPU.
VSWA is a mechanism in which a model’s layers alternate between multiple sliding window sizes. An example of this is Gemma 3, which incorporates both global attention layers and sliding window layers.

<Note>
- Ensure that required services such as `nats` and `etcd` are running before starting.
- Request access to `google/gemma-3-1b-it` on Hugging Face and set your `HF_TOKEN` environment variable for authentication.
</Note>

## Aggregated Serving
```bash
cd $DYNAMO_HOME/examples/backends/trtllm
export MODEL_PATH=google/gemma-3-1b-it
export SERVED_MODEL_NAME=$MODEL_PATH
export AGG_ENGINE_ARGS=$DYNAMO_HOME/examples/backends/trtllm/engine_configs/gemma3/vswa_agg.yaml
./launch/agg.sh
```

## Aggregated Serving with KV Routing
```bash
cd $DYNAMO_HOME/examples/backends/trtllm
export MODEL_PATH=google/gemma-3-1b-it
export SERVED_MODEL_NAME=$MODEL_PATH
export AGG_ENGINE_ARGS=$DYNAMO_HOME/examples/backends/trtllm/engine_configs/gemma3/vswa_agg.yaml
./launch/agg_router.sh
```

## Disaggregated Serving
```bash
cd $DYNAMO_HOME/examples/backends/trtllm
export MODEL_PATH=google/gemma-3-1b-it
export SERVED_MODEL_NAME=$MODEL_PATH
export PREFILL_ENGINE_ARGS=$DYNAMO_HOME/examples/backends/trtllm/engine_configs/gemma3/vswa_prefill.yaml
export DECODE_ENGINE_ARGS=$DYNAMO_HOME/examples/backends/trtllm/engine_configs/gemma3/vswa_decode.yaml
./launch/disagg.sh
```

## Disaggregated Serving with KV Routing
```bash
cd $DYNAMO_HOME/examples/backends/trtllm
export MODEL_PATH=google/gemma-3-1b-it
export SERVED_MODEL_NAME=$MODEL_PATH
export PREFILL_ENGINE_ARGS=$DYNAMO_HOME/examples/backends/trtllm/engine_configs/gemma3/vswa_prefill.yaml
export DECODE_ENGINE_ARGS=$DYNAMO_HOME/examples/backends/trtllm/engine_configs/gemma3/vswa_decode.yaml
./launch/disagg_router.sh
```