LocalAI/docs/content/getting-started/container-images.md

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LocalAI provides a variety of images to support different environments. These images are available on quay.io and Docker Hub.

All-in-One images comes with a pre-configured set of models and backends, standard images instead do not have any model pre-configured and installed.

For GPU Acceleration support for Nvidia video graphic cards, use the Nvidia/CUDA images, if you don't have a GPU, use the CPU images. If you have AMD or Mac Silicon, see the [build section]({{%relref "installation/build" %}}).

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Available Images Types:

• Images ending with -core are smaller images without predownload python dependencies. Use these images if you plan to use llama.cpp, stablediffusion-ncn or rwkv backends - if you are not sure which one to use, do not use these images.
• Images containing the aio tag are all-in-one images with all the features enabled, and come with an opinionated set of configuration.

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Prerequisites

Before you begin, ensure you have a container engine installed if you are not using the binaries. Suitable options include Docker or Podman. For installation instructions, refer to the following guides:

• Install Docker Desktop (Mac, Windows, Linux)
• Install Podman (Linux)
• Install Docker engine (Servers)

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Hardware Requirements: The hardware requirements for LocalAI vary based on the model size and quantization method used. For performance benchmarks with different backends, such as llama.cpp, visit this link. The rwkv backend is noted for its lower resource consumption.

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Standard container images

Standard container images do not have pre-installed models. Use these if you want to configure models manually.

{{< tabs >}} {{% tab title="Vanilla / CPU Images" %}}

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master	localai/localai:master
Latest tag	quay.io/go-skynet/local-ai:latest	localai/localai:latest
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}	localai/localai:{{< version >}}

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{{% tab title="GPU Images CUDA 12" %}}

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-gpu-nvidia-cuda-12	localai/localai:master-gpu-nvidia-cuda-12
Latest tag	quay.io/go-skynet/local-ai:latest-gpu-nvidia-cuda-12	localai/localai:latest-gpu-nvidia-cuda-12
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-gpu-nvidia-cuda-12	localai/localai:{{< version >}}-gpu-nvidia-cuda-12

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{{% tab title="GPU Images CUDA 13" %}}

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-gpu-nvidia-cuda-13	localai/localai:master-gpu-nvidia-cuda-13
Latest tag	quay.io/go-skynet/local-ai:latest-gpu-nvidia-cuda-13	localai/localai:latest-gpu-nvidia-cuda-13
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-gpu-nvidia-cuda-13	localai/localai:{{< version >}}-gpu-nvidia-cuda-13

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{{% tab title="Intel GPU" %}}

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-gpu-intel	localai/localai:master-gpu-intel
Latest tag	quay.io/go-skynet/local-ai:latest-gpu-intel	localai/localai:latest-gpu-intel
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-gpu-intel	localai/localai:{{< version >}}-gpu-intel

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{{% tab title="AMD GPU" %}}

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-gpu-hipblas	localai/localai:master-gpu-hipblas
Latest tag	quay.io/go-skynet/local-ai:latest-gpu-hipblas	localai/localai:latest-gpu-hipblas
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-gpu-hipblas	localai/localai:{{< version >}}-gpu-hipblas

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{{% tab title="Vulkan Images" %}}

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-vulkan	localai/localai:master-vulkan
Latest tag	quay.io/go-skynet/local-ai:latest-gpu-vulkan	localai/localai:latest-gpu-vulkan
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-vulkan	localai/localai:{{< version >}}-vulkan
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{{% tab title="Nvidia Linux for tegra (CUDA 12)" %}}

These images are compatible with Nvidia ARM64 devices with CUDA 12, such as the Jetson Nano, Jetson Xavier NX, and Jetson AGX Orin. For more information, see the [Nvidia L4T guide]({{%relref "reference/nvidia-l4t" %}}).

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-nvidia-l4t-arm64	localai/localai:master-nvidia-l4t-arm64
Latest tag	quay.io/go-skynet/local-ai:latest-nvidia-l4t-arm64	localai/localai:latest-nvidia-l4t-arm64
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-nvidia-l4t-arm64	localai/localai:{{< version >}}-nvidia-l4t-arm64

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{{% tab title="Nvidia Linux for tegra (CUDA 13)" %}}

These images are compatible with Nvidia ARM64 devices with CUDA 13, such as the Nvidia DGX Spark. For more information, see the [Nvidia L4T guide]({{%relref "reference/nvidia-l4t" %}}).

Description	Quay	Docker Hub
Latest images from the branch (development)	quay.io/go-skynet/local-ai:master-nvidia-l4t-arm64-cuda-13	localai/localai:master-nvidia-l4t-arm64-cuda-13
Latest tag	quay.io/go-skynet/local-ai:latest-nvidia-l4t-arm64-cuda-13	localai/localai:latest-nvidia-l4t-arm64-cuda-13
Versioned image	quay.io/go-skynet/local-ai:{{< version >}}-nvidia-l4t-arm64-cuda-13	localai/localai:{{< version >}}-nvidia-l4t-arm64-cuda-13

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All-in-one images

All-In-One images are images that come pre-configured with a set of models and backends to fully leverage almost all the LocalAI featureset. These images are available for both CPU and GPU environments. The AIO images are designed to be easy to use and require no configuration. Models configuration can be found here separated by size.

In the AIO images there are models configured with the names of OpenAI models, however, they are really backed by Open Source models. You can find the table below

Category	Model name	Real model (CPU)	Real model (GPU)
Text Generation	gpt-4	phi-2	hermes-2-pro-mistral
Multimodal Vision	gpt-4-vision-preview	bakllava	llava-1.6-mistral
Image Generation	stablediffusion	stablediffusion	dreamshaper-8
Speech to Text	whisper-1	whisper with whisper-base model	<= same
Text to Speech	tts-1	en-us-amy-low.onnx from rhasspy/piper	<= same
Embeddings	text-embedding-ada-002	all-MiniLM-L6-v2 in Q4	all-MiniLM-L6-v2

Usage

Select the image (CPU or GPU) and start the container with Docker:

docker run -p 8080:8080 --name local-ai -ti localai/localai:latest-aio-cpu

LocalAI will automatically download all the required models, and the API will be available at localhost:8080.

Or with a docker-compose file:

version: "3.9"
services:
  api:
    image: localai/localai:latest-aio-cpu
    # For a specific version:
    # image: localai/localai:{{< version >}}-aio-cpu
    # For Nvidia GPUs decomment one of the following (cuda12 or cuda13):
    # image: localai/localai:{{< version >}}-aio-gpu-nvidia-cuda-12
    # image: localai/localai:{{< version >}}-aio-gpu-nvidia-cuda-13
    # image: localai/localai:latest-aio-gpu-nvidia-cuda-12
    # image: localai/localai:latest-aio-gpu-nvidia-cuda-13
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8080/readyz"]
      interval: 1m
      timeout: 20m
      retries: 5
    ports:
      - 8080:8080
    environment:
      - DEBUG=true
      # ...
    volumes:
      - ./models:/models:cached
    # decomment the following piece if running with Nvidia GPUs
    # deploy:
    #   resources:
    #     reservations:
    #       devices:
    #         - driver: nvidia
    #           count: 1
    #           capabilities: [gpu]

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Models caching: The AIO image will download the needed models on the first run if not already present and store those in /models inside the container. The AIO models will be automatically updated with new versions of AIO images.

You can change the directory inside the container by specifying a MODELS_PATH environment variable (or --models-path).

If you want to use a named model or a local directory, you can mount it as a volume to /models:

docker run -p 8080:8080 --name local-ai -ti -v $PWD/models:/models localai/localai:latest-aio-cpu

or associate a volume:

docker volume create localai-models
docker run -p 8080:8080 --name local-ai -ti -v localai-models:/models localai/localai:latest-aio-cpu

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Available AIO images

Description	Quay	Docker Hub
Latest images for CPU	quay.io/go-skynet/local-ai:latest-aio-cpu	localai/localai:latest-aio-cpu
Versioned image (e.g. for CPU)	quay.io/go-skynet/local-ai:{{< version >}}-aio-cpu	localai/localai:{{< version >}}-aio-cpu
Latest images for Nvidia GPU (CUDA12)	quay.io/go-skynet/local-ai:latest-aio-gpu-nvidia-cuda-12	localai/localai:latest-aio-gpu-nvidia-cuda-12
Latest images for Nvidia GPU (CUDA13)	quay.io/go-skynet/local-ai:latest-aio-gpu-nvidia-cuda-13	localai/localai:latest-aio-gpu-nvidia-cuda-13
Latest images for AMD GPU	quay.io/go-skynet/local-ai:latest-aio-gpu-hipblas	localai/localai:latest-aio-gpu-hipblas
Latest images for Intel GPU	quay.io/go-skynet/local-ai:latest-aio-gpu-intel	localai/localai:latest-aio-gpu-intel

Available environment variables

The AIO Images are inheriting the same environment variables as the base images and the environment of LocalAI (that you can inspect by calling --help). However, it supports additional environment variables available only from the container image

Variable	Default	Description
PROFILE	Auto-detected	The size of the model to use. Available: cpu, gpu-8g
MODELS	Auto-detected	A list of models YAML Configuration file URI/URL (see also [running models]({{%relref "getting-started/models" %}}))

See Also

• [GPU acceleration]({{%relref "features/gpu-acceleration" %}})