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Intel Alderlake gen12 Machine learning doesn't use GPU (intel n100) #4969

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opened 2026-02-05 11:01:48 +03:00 by OVERLORD · 0 comments
OVERLORD commented 2026-02-05 11:01:48 +03:00
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Originally created by @balgerion on GitHub (Dec 19, 2024).

The bug

im trying to install immich with all bells and whistles on my minipc Nas with intel n100 Alderlake gen12 gpu.
Gpu i passed to container (please see scrnshots) but Machine learning is using only CPU for fun.
Installation is on TrueNas ElectricEel-24.10.1 but im using normal docker-compose (not APP from truneas - tried that and result is the same)
{0AD5F181-066A-4D50-92F1-62C17A6210B4}

screenshots from inside machine learning container: (as you can see GPU is not doing much ;) )
{12242CB4-9975-4E06-B37E-DF176AE0AABF}
{0AF96549-4436-4C66-AA27-8B0F7B1A6BCF}

The OS that Immich Server is running on

TrueNas ElectricEel-24.10.1

Version of Immich Server

1.123.0

Version of Immich Mobile App

1.123.0

Platform with the issue

  • Server
  • Web
  • Mobile

Your docker-compose.yml content

name: immich
services:
  immich-server:
    container_name: immich_server
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
    privileged: true
    extends:
      file: hwaccel.transcoding.yml
      service: quicksync # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
    volumes:
      # Do not edit the next line. If you want to change the media storage location on your system, edit the value of UPLOAD_LOCATION in the .env file
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - ${THUMB_LOCATION}:/usr/src/app/upload/thumbs
      - ${ENCODED_VIDEO_LOCATION}:/usr/src/app/upload/encoded-video
      - ${PROFILE_LOCATION}:/usr/src/app/upload/profile
      - ${BACKUP_LOCATION}:/usr/src/app/upload/backups
      - /etc/localtime:/etc/localtime:ro
    env_file:
      - .env
    ports:
      - '2283:2283'
    depends_on:
      - redis
      - database
    restart: always
    healthcheck:
      disable: false

  immich-machine-learning:
    container_name: immich_machine_learning
    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
    # Example tag: ${IMMICH_VERSION:-release}-cuda
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
    privileged: true
    extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
      file: hwaccel.ml.yml
      service: openvino # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-w
    volumes:
      - model-cache:/cache
    env_file:
      - .env
    restart: always
    healthcheck:
      disable: false

  redis:
    container_name: immich_redis
    image: docker.io/redis:6.2-alpine@sha256:eaba718fecd1196d88533de7ba49bf903ad33664a92debb24660a922ecd9cac8
    healthcheck:
      test: redis-cli ping || exit 1
    restart: always

  database:
    container_name: immich_postgres
    image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
    environment:
      POSTGRES_PASSWORD: ${DB_PASSWORD}
      POSTGRES_USER: ${DB_USERNAME}
      POSTGRES_DB: ${DB_DATABASE_NAME}
      POSTGRES_INITDB_ARGS: '--data-checksums'
    volumes:
      # Do not edit the next line. If you want to change the database storage location on your system, edit the value of DB_DATA_LOCATION in the .env file
      - ${DB_DATA_LOCATION}:/var/lib/postgresql/data
    healthcheck:
      test: >-
        pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1;
        Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align
        --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')";
        echo "checksum failure count is $$Chksum";
        [ "$$Chksum" = '0' ] || exit 1
      interval: 5m
      start_interval: 30s
      start_period: 5m
    command: >-
      postgres
      -c shared_preload_libraries=vectors.so
      -c 'search_path="$$user", public, vectors'
      -c logging_collector=on
      -c max_wal_size=2GB
      -c shared_buffers=512MB
      -c wal_compression=on
    restart: always

volumes:
  model-cache:

Your .env content

DB_DATA_LOCATION=/mnt/Balgeriada1/Photos/db
UPLOAD_LOCATION=/mnt/Balgeriada1/Photos/Uploads
THUMB_LOCATION=/mnt/Balgeriada1/Photos/Thumbs
ENCODED_VIDEO_LOCATION=/mnt/Balgeriada1/Photos/Video
PROFILE_LOCATION=/mnt/Balgeriada1/Photos/Profile
BACKUP_LOCATION=/mnt/Balgeriada1/Photos/Backup
TZ=Europe/Warsaw
IMMICH_VERSION=release
DB_PASSWORD=dupa
DB_USERNAME=postgres
DB_DATABASE_NAME=immich


----------------------------------
# Configurations for hardware-accelerated transcoding

# If using Unraid or another platform that doesn't allow multiple Compose files,
# you can inline the config for a backend by copying its contents
# into the immich-microservices service in the docker-compose.yml file.

# See https://immich.app/docs/features/hardware-transcoding for more info on using hardware transcoding.

services:
  cpu: {}

  nvenc:
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities:
                - gpu
                - compute
                - video

  quicksync:
    devices:
      - /dev/dri:/dev/dri

  rkmpp:
    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
      - systempaths=unconfined
      - apparmor=unconfined
    group_add:
      - video
    devices:
      - /dev/rga:/dev/rga
      - /dev/dri:/dev/dri
      - /dev/dma_heap:/dev/dma_heap
      - /dev/mpp_service:/dev/mpp_service
      #- /dev/mali0:/dev/mali0 # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
    volumes:
      #- /etc/OpenCL:/etc/OpenCL:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
      #- /usr/lib/aarch64-linux-gnu/libmali.so.1:/usr/lib/aarch64-linux-gnu/libmali.so.1:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping

  vaapi:
    devices:
      - /dev/dri:/dev/dri

  vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2
    devices:
      - /dev/dri:/dev/dri
    volumes:
      - /usr/lib/wsl:/usr/lib/wsl
    environment:
      - LIBVA_DRIVER_NAME=d3d12


and both hwacell files: 
-----------------------------
# Configurations for hardware-accelerated machine learning

# If using Unraid or another platform that doesn't allow multiple Compose files,
# you can inline the config for a backend by copying its contents
# into the immich-machine-learning service in the docker-compose.yml file.

# See https://immich.app/docs/features/ml-hardware-acceleration for info on usage.

services:
  armnn:
    devices:
      - /dev/mali0:/dev/mali0
    volumes:
      - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
      - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)

  cpu: {}

  cuda:
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities:
                - gpu

  openvino:
    device_cgroup_rules:
      - 'c 189:* rmw'
    devices:
      - /dev/dri:/dev/dri
    volumes:
      - /dev/bus/usb:/dev/bus/usb

  openvino-wsl:
    devices:
      - /dev/dri:/dev/dri
      - /dev/dxg:/dev/dxg
    volumes:
      - /dev/bus/usb:/dev/bus/usb
      - /usr/lib/wsl:/usr/lib/wsl

Reproduction steps

  1. normal installation - step by step instruction from site

...

Relevant log output

No response

Additional information

No response

Originally created by @balgerion on GitHub (Dec 19, 2024). ### The bug im trying to install immich with all bells and whistles on my minipc Nas with intel n100 Alderlake gen12 gpu. Gpu i passed to container (please see scrnshots) but Machine learning is using only CPU for fun. Installation is on TrueNas ElectricEel-24.10.1 but im using normal docker-compose (not APP from truneas - tried that and result is the same) ![{0AD5F181-066A-4D50-92F1-62C17A6210B4}](https://github.com/user-attachments/assets/155b589c-6508-419b-b528-ae8e63070a7c) screenshots from inside machine learning container: (as you can see GPU is not doing much ;) ) ![{12242CB4-9975-4E06-B37E-DF176AE0AABF}](https://github.com/user-attachments/assets/9306d99f-6e36-4cef-a8c8-0439121c738f) ![{0AF96549-4436-4C66-AA27-8B0F7B1A6BCF}](https://github.com/user-attachments/assets/52c2d461-62a8-4101-befb-824cdc867d37) ### The OS that Immich Server is running on TrueNas ElectricEel-24.10.1 ### Version of Immich Server 1.123.0 ### Version of Immich Mobile App 1.123.0 ### Platform with the issue - [X] Server - [ ] Web - [ ] Mobile ### Your docker-compose.yml content ```YAML name: immich services: immich-server: container_name: immich_server image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release} privileged: true extends: file: hwaccel.transcoding.yml service: quicksync # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding volumes: # Do not edit the next line. If you want to change the media storage location on your system, edit the value of UPLOAD_LOCATION in the .env file - ${UPLOAD_LOCATION}:/usr/src/app/upload - ${THUMB_LOCATION}:/usr/src/app/upload/thumbs - ${ENCODED_VIDEO_LOCATION}:/usr/src/app/upload/encoded-video - ${PROFILE_LOCATION}:/usr/src/app/upload/profile - ${BACKUP_LOCATION}:/usr/src/app/upload/backups - /etc/localtime:/etc/localtime:ro env_file: - .env ports: - '2283:2283' depends_on: - redis - database restart: always healthcheck: disable: false immich-machine-learning: container_name: immich_machine_learning # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag. # Example tag: ${IMMICH_VERSION:-release}-cuda image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release} privileged: true extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration file: hwaccel.ml.yml service: openvino # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-w volumes: - model-cache:/cache env_file: - .env restart: always healthcheck: disable: false redis: container_name: immich_redis image: docker.io/redis:6.2-alpine@sha256:eaba718fecd1196d88533de7ba49bf903ad33664a92debb24660a922ecd9cac8 healthcheck: test: redis-cli ping || exit 1 restart: always database: container_name: immich_postgres image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0 environment: POSTGRES_PASSWORD: ${DB_PASSWORD} POSTGRES_USER: ${DB_USERNAME} POSTGRES_DB: ${DB_DATABASE_NAME} POSTGRES_INITDB_ARGS: '--data-checksums' volumes: # Do not edit the next line. If you want to change the database storage location on your system, edit the value of DB_DATA_LOCATION in the .env file - ${DB_DATA_LOCATION}:/var/lib/postgresql/data healthcheck: test: >- pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1; Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')"; echo "checksum failure count is $$Chksum"; [ "$$Chksum" = '0' ] || exit 1 interval: 5m start_interval: 30s start_period: 5m command: >- postgres -c shared_preload_libraries=vectors.so -c 'search_path="$$user", public, vectors' -c logging_collector=on -c max_wal_size=2GB -c shared_buffers=512MB -c wal_compression=on restart: always volumes: model-cache: ``` ### Your .env content ```Shell DB_DATA_LOCATION=/mnt/Balgeriada1/Photos/db UPLOAD_LOCATION=/mnt/Balgeriada1/Photos/Uploads THUMB_LOCATION=/mnt/Balgeriada1/Photos/Thumbs ENCODED_VIDEO_LOCATION=/mnt/Balgeriada1/Photos/Video PROFILE_LOCATION=/mnt/Balgeriada1/Photos/Profile BACKUP_LOCATION=/mnt/Balgeriada1/Photos/Backup TZ=Europe/Warsaw IMMICH_VERSION=release DB_PASSWORD=dupa DB_USERNAME=postgres DB_DATABASE_NAME=immich ---------------------------------- # Configurations for hardware-accelerated transcoding # If using Unraid or another platform that doesn't allow multiple Compose files, # you can inline the config for a backend by copying its contents # into the immich-microservices service in the docker-compose.yml file. # See https://immich.app/docs/features/hardware-transcoding for more info on using hardware transcoding. services: cpu: {} nvenc: deploy: resources: reservations: devices: - driver: nvidia count: 1 capabilities: - gpu - compute - video quicksync: devices: - /dev/dri:/dev/dri rkmpp: security_opt: # enables full access to /sys and /proc, still far better than privileged: true - systempaths=unconfined - apparmor=unconfined group_add: - video devices: - /dev/rga:/dev/rga - /dev/dri:/dev/dri - /dev/dma_heap:/dev/dma_heap - /dev/mpp_service:/dev/mpp_service #- /dev/mali0:/dev/mali0 # only required to enable OpenCL-accelerated HDR -> SDR tonemapping volumes: #- /etc/OpenCL:/etc/OpenCL:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping #- /usr/lib/aarch64-linux-gnu/libmali.so.1:/usr/lib/aarch64-linux-gnu/libmali.so.1:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping vaapi: devices: - /dev/dri:/dev/dri vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2 devices: - /dev/dri:/dev/dri volumes: - /usr/lib/wsl:/usr/lib/wsl environment: - LIBVA_DRIVER_NAME=d3d12 and both hwacell files: ----------------------------- # Configurations for hardware-accelerated machine learning # If using Unraid or another platform that doesn't allow multiple Compose files, # you can inline the config for a backend by copying its contents # into the immich-machine-learning service in the docker-compose.yml file. # See https://immich.app/docs/features/ml-hardware-acceleration for info on usage. services: armnn: devices: - /dev/mali0:/dev/mali0 volumes: - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver) - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required) cpu: {} cuda: deploy: resources: reservations: devices: - driver: nvidia count: 1 capabilities: - gpu openvino: device_cgroup_rules: - 'c 189:* rmw' devices: - /dev/dri:/dev/dri volumes: - /dev/bus/usb:/dev/bus/usb openvino-wsl: devices: - /dev/dri:/dev/dri - /dev/dxg:/dev/dxg volumes: - /dev/bus/usb:/dev/bus/usb - /usr/lib/wsl:/usr/lib/wsl ``` ### Reproduction steps 1. normal installation - step by step instruction from site 2. 3. ... ### Relevant log output _No response_ ### Additional information _No response_
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Reference: immich-app/immich#4969
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