There are three ways to install Miles. Docker is recommended because Miles pins patched
versions of SGLang, Megatron-LM, and a few CUDA kernels.
Method 1: Docker (recommended)
NVIDIA
AMD MI300X / MI350X
docker pull radixark/miles:latest
docker run --rm \
--gpus all --ipc=host --shm-size=32g \
--ulimit memlock=-1 --ulimit stack=67108864 \
--network=host \
-it radixark/miles:latest /bin/bash
docker pull rlsys/miles:MI350-355-latest # or MI300-latest
docker run --rm \
--device /dev/dri --device /dev/kfd \
--group-add video --ipc=host --shm-size=32g \
--cap-add SYS_PTRACE --security-opt seccomp=unconfined \
--privileged \
-it rlsys/miles:MI350-355-latest /bin/bash
- PyTorch (matching the container’s CUDA / ROCm version)
- Megatron-LM, SGLang, FlashAttention-3, DeepGEMM, Apex
- Ray, uv, and Miles installed editable at
/root/miles
See Platforms for platform-specific notes.
Method 2: From source
Clone and install in an existing environment.
git clone https://github.com/radixark/miles.git
cd miles
pip install -r requirements.txt
pip install -e . --no-deps
Patched dependencies. Miles pins patched versions of SGLang and Megatron-LM. Installing them yourself at
the wrong commit is the most common source of bug reports — use Docker if you can.
Method 3: Update an existing container
If you already run a Miles image and want the latest code:
cd /root/miles
git pull --rebase
pip install -e . --no-deps
ray stop && ray start --head --port=6379
Verify
Confirm Miles imports and the GPUs are visible:
python -c "import miles; print('Miles import OK')"
nvidia-smi
Hardware requirements
| Hardware | Status |
|---|
| NVIDIA H100 / H200 | Production (CI guarded) |
| NVIDIA B100 / B200 | Production |
| NVIDIA A100 | Supported — FP8 features disabled |
| AMD MI300X, MI325, MI350X, MI355X | Supported via ROCm |
Next steps
