docs(trtllm): Update the trtllm installation instructions (#11066)

Co-authored-by: Ryan McCormick <rmccormick@nvidia.com>

Author: tanmayv25

docs/getting-started/local-installation.md

@@ -55,6 +55,8 @@ versions and backend guides for run instructions: [SGLang](../backends/sglang/RE
 
 ### Option B: Install from PyPI
 
+Supported for vLLM and SGLang only. Use Option A for TensorRT-LLM.
+
 ```bash
 # Install uv (recommended Python package manager)
 curl -LsSf https://astral.sh/uv/install.sh | sh
@@ -77,19 +79,6 @@ uv pip install --prerelease=allow "ai-dynamo[sglang]"
 For CUDA 13 (B300/GB300), the container is recommended. See
 [SGLang install docs](https://docs.sglang.io/get_started/install.html) for details.
 
-**TensorRT-LLM**
-
-```bash
-sudo apt install python3-dev
-pip install torch==2.9.0 torchvision --index-url https://download.pytorch.org/whl/cu130
-pip install --pre --extra-index-url https://pypi.nvidia.com "ai-dynamo[trtllm]"
-```
-
-TensorRT-LLM requires `pip` due to a transitive Git URL dependency that
-`uv` doesn't resolve. We recommend using the TensorRT-LLM container for
-broader compatibility. See the [TRT-LLM backend guide](../backends/trtllm/README.md)
-for details.
-
 **vLLM**
 
 ```bash
@@ -207,9 +196,10 @@ The default model `Qwen/Qwen3-0.6B` requires ~2GB of GPU memory. Larger models n
 
 Start with a small model and scale up based on your hardware.
 
-**Python 3.11 with TensorRT-LLM**
+**TensorRT-LLM**
 
-TensorRT-LLM does not support Python 3.11. If you see installation failures with TensorRT-LLM, check your Python version with `python3 --version`. Use Python 3.10 or 3.12 instead.
+TensorRT-LLM is not supported via a local PyPI install. Use the
+`tensorrtllm-runtime` container (Option A).
 
 **Container runs but GPU not detected**
 

docs/getting-started/local-installation.zh-CN.md

@@ -57,6 +57,8 @@ docker run --gpus all --network host --rm -it nvcr.io/nvidia/ai-dynamo/vllm-runt
 
 ### 选项 B：从 PyPI 安装
 
+仅支持 vLLM 和 SGLang。TensorRT-LLM 请使用选项 A。
+
 ```bash
 # Install uv (recommended Python package manager)
 curl -LsSf https://astral.sh/uv/install.sh | sh
@@ -79,18 +81,6 @@ uv pip install --prerelease=allow "ai-dynamo[sglang]"
 对于 CUDA 13（B300/GB300），推荐使用容器。详情请参阅
 [SGLang 安装文档](https://docs.sglang.io/get_started/install.html)。
 
-**TensorRT-LLM**
-
-```bash
-sudo apt install python3-dev
-pip install torch==2.9.0 torchvision --index-url https://download.pytorch.org/whl/cu130
-pip install --pre --extra-index-url https://pypi.nvidia.com "ai-dynamo[trtllm]"
-```
-
-由于传递性 Git URL 依赖项 `uv` 无法解析，TensorRT-LLM 需要使用 `pip`。
-为获得更广泛的兼容性，我们建议使用 TensorRT-LLM 容器。
-详情请参阅 [TRT-LLM 后端指南](../backends/trtllm/README.md)。
-
 **vLLM**
 
 ```bash
@@ -209,7 +199,8 @@ curl localhost:8000/v1/chat/completions \
 
 **TensorRT-LLM 与 Python 3.11**
 
-TensorRT-LLM 不支持 Python 3.11。如果你在安装 TensorRT-LLM 时看到失败，请使用 `python3 --version` 检查 Python 版本。请改用 Python 3.10 或 3.12。
+TensorRT-LLM 仅支持容器路径。请使用 `tensorrtllm-runtime`
+容器（选项 A）。
 
 **容器运行但未检测到 GPU**
 

docs/reference/release-artifacts.md

@@ -37,7 +37,8 @@ Release history in this document begins at v0.6.0.
 
 ### Python Wheels
 
-We recommend using the TensorRT-LLM NGC container instead of the `ai-dynamo[trtllm]` wheel. See the [NGC container collection](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/collections/ai-dynamo) for supported images.
+For TensorRT-LLM, use the NGC container — not the `ai-dynamo[trtllm]` PyPI extra.
+See the [NGC container collection](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-dynamo/collections/ai-dynamo).
 
 | Package | Description | Python | Platform | PyPI |
 |---------|-------------|--------|----------|------|
@@ -106,11 +107,12 @@ docker pull nvcr.io/nvidia/ai-dynamo/snapshot-agent:1.2.1
 > For detailed installation instructions, see the [Quickstart](https://docs.nvidia.com/dynamo/getting-started/quickstart) in the docs.
 
 ```bash
-# Install Dynamo with a specific backend (Recommended)
+# Install Dynamo with a specific backend (vLLM and SGLang)
 uv pip install "ai-dynamo[vllm]==1.2.1"
 uv pip install --prerelease=allow "ai-dynamo[sglang]==1.2.1"
-# TensorRT-LLM requires the NVIDIA PyPI index and pip
-pip install --pre --extra-index-url https://pypi.nvidia.com "ai-dynamo[trtllm]==1.2.1"
+
+# TensorRT-LLM: use container (see above)
+docker pull nvcr.io/nvidia/ai-dynamo/tensorrtllm-runtime:1.2.1
 
 # Install Dynamo core only
 uv pip install ai-dynamo==1.2.1