diff --git a/docs/content/docs/features/GPU-acceleration.md b/docs/content/docs/features/GPU-acceleration.md
index cef08e71fb62..7d1f7e2e81ef 100644
--- a/docs/content/docs/features/GPU-acceleration.md
+++ b/docs/content/docs/features/GPU-acceleration.md
@@ -15,9 +15,45 @@ This section contains instruction on how to use LocalAI with GPU acceleration.
 For accelleration for AMD or Metal HW there are no specific container images, see the [build]({{%relref "docs/getting-started/build#Acceleration" %}})
 {{% /alert %}}
 
-### CUDA(NVIDIA) acceleration
 
-#### Requirements
+## Model configuration
+
+Depending on the model architecture and backend used, there might be different ways to enable GPU acceleration. It is required to configure the model you intend to use with a YAML config file. For example, for `llama.cpp` workloads a configuration file might look like this (where `gpu_layers` is the number of layers to offload to the GPU):
+
+```yaml
+name: my-model-name
+# Default model parameters
+parameters:
+  # Relative to the models path
+  model: llama.cpp-model.ggmlv3.q5_K_M.bin
+
+context_size: 1024
+threads: 1
+
+f16: true # enable with GPU acceleration
+gpu_layers: 22 # GPU Layers (only used when built with cublas)
+
+```
+
+For diffusers instead, it might look like this instead:
+
+```yaml
+name: stablediffusion
+parameters:
+  model: toonyou_beta6.safetensors
+backend: diffusers
+step: 30
+f16: true
+diffusers:
+  pipeline_type: StableDiffusionPipeline
+  cuda: true
+  enable_parameters: "negative_prompt,num_inference_steps,clip_skip"
+  scheduler_type: "k_dpmpp_sde"
+```
+
+## CUDA(NVIDIA) acceleration
+
+### Requirements
 
 Requirement: nvidia-container-toolkit (installation instructions [1](https://www.server-world.info/en/note?os=Ubuntu_22.04&p=nvidia&f=2) [2](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html))
 
@@ -74,37 +110,24 @@ llama_model_load_internal: total VRAM used: 1598 MB
 llama_init_from_file: kv self size  =  512.00 MB
 ```
 
-#### Model configuration
+## Intel acceleration (sycl)
 
-Depending on the model architecture and backend used, there might be different ways to enable GPU acceleration. It is required to configure the model you intend to use with a YAML config file. For example, for `llama.cpp` workloads a configuration file might look like this (where `gpu_layers` is the number of layers to offload to the GPU):
+#### Requirements
 
-```yaml
-name: my-model-name
-# Default model parameters
-parameters:
-  # Relative to the models path
-  model: llama.cpp-model.ggmlv3.q5_K_M.bin
+Requirement: [Intel oneAPI Base Toolkit](https://software.intel.com/content/www/us/en/develop/tools/oneapi/base-toolkit/download.html)
 
-context_size: 1024
-threads: 1
+To use SYCL, use the images with the `sycl` tag, for example.
 
-f16: true # enable with GPU acceleration
-gpu_layers: 22 # GPU Layers (only used when built with cublas)
+The image list is on [quay](https://quay.io/repository/go-skynet/local-ai?tab=tags):
 
-```
+- SYCL tags: `master-sycl`, `v1.40.0-sycl`, ...
+- SYCL + FFmpeg tags: `master-sycl-ffmpeg`, `v1.40.0-sycl-ffmpeg`, ...
 
-For diffusers instead, it might look like this instead:
+### Notes
+
+In addition to the commands to run LocalAI normally, you need to specify `--device /dev/dri` to docker, for example:
+
+```bash
+docker run --rm -ti --device /dev/dri -p 8080:8080 -e DEBUG=true -e MODELS_PATH=/models -e THREADS=1 -v $PWD/models:/models quay.io/go-skynet/local-ai:v1.40.0-sycl
+```
 
-```yaml
-name: stablediffusion
-parameters:
-  model: toonyou_beta6.safetensors
-backend: diffusers
-step: 30
-f16: true
-diffusers:
-  pipeline_type: StableDiffusionPipeline
-  cuda: true
-  enable_parameters: "negative_prompt,num_inference_steps,clip_skip"
-  scheduler_type: "k_dpmpp_sde"
-```
\ No newline at end of file
diff --git a/docs/content/docs/getting-started/build.md b/docs/content/docs/getting-started/build.md
index c2a7e0eef8b3..b26a16d7e8c4 100644
--- a/docs/content/docs/getting-started/build.md
+++ b/docs/content/docs/getting-started/build.md
@@ -83,7 +83,7 @@ Here is the list of the variables available that can be used to customize the bu
 
 | Variable | Default | Description |
 | ---------------------| ------- | ----------- |
-| `BUILD_TYPE`         |   None      | Build type. Available: `cublas`, `openblas`, `clblas`, `metal`,`hipblas` |
+| `BUILD_TYPE`         |   None      | Build type. Available: `cublas`, `openblas`, `clblas`, `metal`,`hipblas`, `sycl_f16`, `sycl_f32` |
 | `GO_TAGS`            |   `tts stablediffusion`      | Go tags. Available: `stablediffusion`, `tts`, `tinydream` |
 | `CLBLAST_DIR`        |         | Specify a CLBlast directory |
 | `CUDA_LIBPATH`       |         | Specify a CUDA library path |
@@ -225,6 +225,17 @@ make BUILD_TYPE=clblas build
 
 To specify a clblast dir set: `CLBLAST_DIR`
 
+#### Intel GPU acceleration
+
+Intel GPU acceleration is supported via SYCL.
+
+Requirements: [Intel oneAPI Base Toolkit](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit-download.html) (see also [llama.cpp setup installations instructions](https://github.com/ggerganov/llama.cpp/blob/d71ac90985854b0905e1abba778e407e17f9f887/README-sycl.md?plain=1#L56))
+
+```
+make BUILD_TYPE=sycl_f16 build # for float16
+make BUILD_TYPE=sycl_f32 build # for float32
+```
+
 #### Metal (Apple Silicon)
 
 ```