Strata-AMD
Docker app from Aurial's Repository
Overview
Readme
View on GitHubStrata AMD for Unraid
An Unraid Community Applications template for the AMD (ROCm) builds of Strata, which runs the Qwen3.8-Flash-Next mixture-of-experts model on an AMD GPU plus system RAM. It serves an OpenAI- and Anthropic-compatible API, a chat page and a live monitor.
The template runs Strata's official image, ghcr.io/niko1221/strata:latest-rocm-gfx120x. Report template or Unraid
problems in this repository's issues, and problems with
Strata itself to the Strata project.
Why a separate listing
The Community Apps catalog already lists Strata, an NVIDIA-only template by
williamkunz (CUDA images, Nvidia Driver plugin, --runtime=nvidia).
That template cannot run on AMD cards. This listing covers the AMD side of the same upstream project: different image
flavors (rocm-gfx120x / rocm-gfx110x / rocm-gfx1151), different host requirements (the amdgpu kernel driver
Unraid already ships — no driver plugin), and device passthrough via /dev/kfd and /dev/dri instead of the NVIDIA
runtime. Both templates use Strata's official image and expose the same settings.
Install
Search for Strata AMD in the Apps tab. Before installing you need:
an AMD card from one of the families Strata publishes images for. At install, pick your card under Branch — the template offers all three ROCm flavors as a dropdown:
Branch shown at install Card latest-rocm-gfx120x(default)RX 9000 series, Radeon AI PRO R9700 (RDNA 4) latest-rocm-gfx110xRX 7000 series (RDNA 3) latest-rocm-gfx1151Ryzen AI Max "Strix Halo" (Radeon 8060S) The RX 6000 series has no image yet. The host needs only the
amdgpukernel driver (Linux 6.8+), which Unraid ships as standard — no driver plugin to install.32 GB of RAM or more; more RAM allows a larger, better model (Strata's model guide)
room for the model on an SSD pool, mapped as a direct pool path (
/mnt/cache/...), not/mnt/user
Do not set a memory limit on the container: Strata plans from the server's whole RAM. Do not pin CPUs: the engine sets its own thread affinity.
The first start downloads the model and prepares it. Later starts go straight to serving. The template's Overview explains each setting, and Strata's Docker guide covers them in full.
An API key is always on. If you leave it empty, the first start makes one; show it with:
docker exec "Strata AMD" strata launch --show-key --preset docker
(The container name contains a space, so quote it.)
Multi-GPU
The GPUs field takes the card numbers as the monitor lists them (0,1 splits the model across both by layer
parallelism), or all / empty for the engine's choice. Every named card must match the Branch family. Under Advanced
there is a GPU roles field for finer control (1=main,0=helper): main runs the final stage the answer comes
from, helper holds a share of the model's layers, off leaves a card alone; cards you do not name are off, and
Strata's automatic choice (faster card as main) is right for almost everyone. A split adds capacity more than
speed — see Strata's multi-GPU guide.
Updates
The template follows latest-rocm-gfx120x, which Strata's maintainer moves to each new release when its image is
published; the same holds for the other two Branch tags. Unraid shows the update on the Docker tab for whichever
branch you installed. To stay on one release, change the Repository tag to a version such as 0.2.7-rocm-gfx120x.
Credits and licence
Strata and its images are by Niko1221 and the Strata contributors, under the MIT licence. The icon is Strata's own. This template follows the structure of the NVIDIA strata-docker template by William Kunz (MIT). This repository is MIT licensed; see LICENSE.
Requirements
amdgpu kernel driver — Unraid ships it, no driver plugin needed (Linux 6.8+). An RDNA 3 / RDNA 4 / Strix Halo card: RX 7000 series, RX 9000 series, Radeon AI PRO R9700, or Ryzen AI Max — pick the matching Branch at install (gfx120x / gfx110x / gfx1151); the RX 6000 series has no image yet. Do not set a memory limit on the container: Strata plans from the server's whole RAM. Do not pin CPUs: the engine sets its own thread affinity.
Categories
Related apps
Explore more like this
Explore allDetails
ghcr.io/niko1221/strata:latest-rocm-gfx120xRuntime arguments
- Web UI
http://[IP]:[PORT:8080]/- Network
bridge- Shell
bash- Privileged
- false
- Extra Params
--device /dev/kfd --device /dev/dri --group-add video --group-add render --ulimit memlock=-1:-1 --shm-size=2g --stop-timeout 120
Template configuration
Chat page, monitor and the API (/v1 for OpenAI clients, the root URL for Anthropic clients).
- Target
- 8080
- Default
- 8080
- Value
- 8080
The model, the prepared pack, presets, tuning and the API key: tens of GB, the log names the size. Use a direct pool path (/mnt/cache/... or /mnt/POOLNAME/...), not /mnt/user: the engine reads the model files while it runs.
- Target
- /data
- Default
- /mnt/cache/appdata/strata-amd
- Value
- /mnt/cache/appdata/strata-amd
The cards the engine uses: numbers as the monitor lists them (0, or 0,1 to split the model across both), or all / empty for the engine's choice. Every named card must match the card family of the Branch.
- Target
- GPUS
- Default
- all
- Value
- all
Advanced, multi-card only: a role for each card, like 1=main,0=helper. main runs the final stage (the answer head; Strata picks the faster card by default), helper shares the model's layers, off leaves the card alone; cards you do not name are off. Not together with GPUs. Empty: Strata chooses.
- Target
- GPU_ROLES
Empty: Strata picks the model it recommends for this server and says so in the log. Or a size such as IQ2_XS, IQ3_XXS, IQ3_S or Q2_0; see docs/MODELS.md in the Strata repository for what each needs.
- Target
- MODEL
Empty for the usual one. qwen, swift (thinks shorter) or coder, when the size exists in several families.
- Target
- FAMILY
How much text it remembers at once. Longer costs RAM.
- Target
- CONTEXT
- Default
- 32k|64k|128k|256k
- Value
- 32k
on: the model reads pictures (about 0.9 GB more to download). gpu or cpu choose where the picture reader runs.
- Target
- VISION
- Default
- off|on|gpu|cpu
- Value
- off
16 characters or more (openssl rand -hex 24 makes one). Empty: the first start makes one and keeps it in the Data folder.
- Target
- API_KEY
Measures the best engine settings for this server, once, and keeps them. quick takes up to about 20 minutes on the first start, thorough up to about 2 hours.
- Target
- TUNE
- Default
- skip|quick|thorough
- Value
- skip
1 tunes again on the next start even if this preset is already tuned, for example after an update. Set it back to 0 afterwards.
- Target
- RETUNE
- Default
- 0|1
- Value
- 0
Requests answered at the same time, 1 to 8. Empty: fitted to the card.
- Target
- PARALLEL
Conversation memory format: int8 (default), q4_0 (half the memory), k8v4, fp16.
- Target
- KV
- Default
- int8|q4_0|k8v4|fp16
- Value
- int8
GGUF files you already have, as a path inside the container. Add a Path mapping for their folder (read-only is fine), e.g. /models, and enter that here; set Model too. Nothing is downloaded for the model itself.
- Target
- MODEL_PATH
Advanced engine settings, space separated, like strata launch --set.
- Target
- STRATA_SET