Welcome to AI Playground open source project and AI PC generative AI application suite. This application provides a full suite of generative AI features for chat, image generation, video generation, code assistance, document search, image analysis, and more. Features can run offline on your PC’s Intel® Core™ Ultra with built-in Intel Arc GPU, Intel Arc™ dGPU Series A or B with 8GB+ of vRAM, or NVIDIA RTX GPUs—or you can optionally use Hybrid Cloud mode to run frontier models from providers such as ChatGPT, Claude, Gemini, and Grok while you manage models, cost, and control of your data.
AI Playground is intended to act as an offline alternative to cloud tools such as Gemini, ChatGPT, and Grok. AI Playground leverages libraries from GitHub and Huggingface including:
- Image Diffusion (PyTorch): Stable Diffusion 1.5, SDXL, Flux.1-Schnell, Flux.1 Kontext[dev], Flux.2 Klein, Z-Image, ERNIE-Image, Wan 2.1/2.2, LTX-Video, LTX-2.3
- LLM: GGUF (Llama.cpp Vulkan) - Gemma 4, Qwen3.5, Qwen3.6, Qwen3 VL, GPT-OSS 20B, DeepSeek R1 Distilled, Phi3, Mistral 7B, Llama 3.2: OpenVINO - TinyLlama, Mistral 7B, Phi3 mini, Phi3.5 mini, DeepSeek R1 Distill (1.5B, 7B). Optional Hybrid Cloud backends connect to hosted models via your API keys.
As a local alternative to cloud AI services, AI Playground is intended to give consumers and AI curious prosumers easy and intuitive access to a wide variety of generative AI features using their Intel powered AI PC. This means you can be offline, without loading sensitive or personal data to 3rd party sites, for free, in a single app without having to know how to install and manage multiple AI backend frameworks. Key features:
- Chat Assistant: One preset for vision, reasoning, document RAG, tool calling, and MCP—run image, video, and editing workflows from chat when tools are enabled
- Latest chat models: Gemma 4, Qwen3.5, Qwen3.6, Qwen3 VL, Mistral 7B, DeepSeek R1, GPT-OSS, and more via Llama.cpp or OpenVINO; browse, favorite, and download from the Model Manager (cylinder icon in the title bar)
- Game Agent & Quick Coder: Agentic presets to create HTML games (plan, debug, play-test, and thumbnails with Game Agent; faster one-shot creation with Quick Coder)
- Audio mode: Speech-to-text and text-to-speech presets (including voice design and custom voices)
- Hybrid Cloud (optional): Use frontier models from top providers when you configure API keys in the Set Up wizard—local features still work without it

Image generation presets Image editing presets Video generation presets
- Agentic chat & MCP: Tool calling connects chat to built-in media tools and external apps (for example Blender via MCP)
Figure 1: Screenshot of user interface with the light color theme and Chat History Panel and Footer Panel exposed
Figure 2: Screenshot of user interface using the default color theme, with the App Settings Panel and Prompt Settings Panel exposed
- English (readme.md)
AI Playground alpha and beta installers are currently available downloadable executables, or available as a source code from our Github repository. To run AI Playground you must have a PC that meets the following specifications
- Windows OS or Linux Ubuntu
- AI Playground Essentials: Intel Core Series 3 with 12GB of system memory (basic chat, RAG chat, basic image gen and editing)
- AI Playground Studio: Intel Core Ultra (Series 3, Series 2 V/H, or Series 1 H) or Intel Arc discrete GPU (Series A or B) with at least 8GB of vRAM (full feature set in the Users Guide)
- AI Playground Studio for NVIDIA CUDA: PC with NVIDIA GeForce RTX discrete GPU with 8GB+ of vRAM (experimental; OpenVINO is not supported in this mode)
- 82GB+ of disk space recommended (application ~6GB; models require additional space)
- Home Agent feature requires a minimum of 32GB of system memory on Intel Core Ultra laptops, or 16GB of vRAM on discrete GPU systems
This is a single packaged installer for all supported hardware mentioned above. This installer simplifies the process for end users to install AI Playground on their PCs. Please note that while this makes the installation process easier, this is open-source beta software, and there may be component and version conflicts. Refer to the Troubleshooting section for known issues.
🆕 AI Playground 3.2.0 beta (all SKUs) - Release Notes | Windows Installer | Linux Installer
Previous release: AI Playground 3.1.2 beta-hf3
- The packaged installer targets all supported hardware above and prepares the AI Playground runtime for first launch.
- On first run, the AI Playground Set Up wizard appears. Choose a hardware mode (Essentials, Studio, or Studio for NVIDIA CUDA) and install backend components (Llama.cpp, OpenVINO, ComfyUI, and optional Home Agent, Hybrid Cloud, and Audio). It is recommended to keep default hardware settings and enable all components, then click Install and Continue. This step needs a clear, unfiltered internet connection (corporate VPNs often cause failures) and may take several minutes.
- Download the Users Guide for full application information: AI Playground Users Guide v3.2
The following are known situations where your installation may be blocked or interrupted. Review the following to remedy installations issues. If installation issues persist, generate a copy of the log by typing CTRL+SHIFT+I, select the console tab and copy the last few entries of the log written where the installer failed. Provide these details to us via the issues tab here, or via the Intel Insiders Discord, or Graphics forum on Intel's support site.
- Llama.cpp embedding issues: At the time of this release, Llama.cpp embeddings may have issues with:
- Recent drivers, and may require DDU to clean driver cache.
- Anti-Virus software - features needed to read and write embedding cache may not be properly installed: Disable anti-virus, restart
- Restart: Time-out issues have been sighted, which show as a failed install but resolve when restarting AI Playground
- Verify Intel Arc GPU: Ensure your system has an Intel Arc GPU with the lastest driver. Go to your Windows Start Menu, type "Device Manager," and under Display Adapters, check the name of your GPU device. It should describe an Intel Arc GPU. If so, then you you have a GPU that means our minimum specifications. If it says "Intel(R) Graphics," your system does not have a built-in Intel Arc GPU and does not meet the minimum specifications. If your GPU is an discrete GPU such as Intel Arc A or B series GPU, then you can troubleshoot a troubled installation by disabling the iGPU in Device Manager
- Interrupted Installation: The online installation for backend components can be interrupted or blocked by an IT network, firewall, corporate VPN, or sleep settings. Disconnect from corporate VPN for the Set Up wizard when possible; otherwise use an open network, with the firewall off, and set sleep settings to stay awake when powered on.
- Missing Libraries: Some Windows systems may be missing needed libraries. This can be fixed by installing the 64-bit VC++ redistribution from Microsoft here. It is recommended this be done after updating the Graphics drivers. Then install AI Playground.
- Python Conflict: Some PCs with an existing installation of Python can cause a conflict with AI Playground installation, where the wrong or conflicting packages are installed due to the incorrect version or location of Python on the system. This is usually remedied by uninstalling Python environment, restarting and reinstalling AI Playground
- Temp Files: Should the installation be interrupted because of any of the above issues it is possible that temporary installation files have been left behind and trying to install with these files in place can block the installation. Remove these files or do a clean install of AI Playground to remedy
To get started, clone the repository and navigate to the project directory:
git clone -b dev https://github.com/intel/AI-Playground.git
cd AI-Playground-
Install the Node.js ≥ 20 development environment.
-
Windows / macOS: download the installer from Node.js.
-
Ubuntu 24.04 / Debian: the distro's
apt install nodejsships Node 18 (nonpm) and is too old. Install Node 22 LTS via NodeSource instead:curl -fsSL https://deb.nodesource.com/setup_22.x | sudo -E bash - sudo apt install -y nodejs node --version # expect: v22.x npm --version # expect: 10.x
Behind a corporate proxy that intercepts
deb.nodesource.com, prefix thecurlwith--proxy "$http_proxy"and ensurehttps_proxyis exported.
-
-
Navigate to the
WebUIdirectory and run the one-time setup:
cd WebUI
npm run setupThis installs the Node.js dependencies, fetches external resources (uv, 7-Zip
and other tools — see Fetch External Resources
below), provisions the Electron binary, and installs the git pre-commit hook
(Ruff for the Python backends, ESLint + Prettier for the WebUI — see
.pre-commit-config.yaml). The hook step is best effort: if pre-commit is
unavailable it prints how to install it and continues. You can re-run just the
hook install at any time with npm run install-hooks. (Plain npm install
still works if you only want the Node.js dependencies.)
- In the
WebUIdirectory, execute thefetch-external-resourcesscript to download required external resources:
This will download uv (Python package manager) and other required tools to the build/resources/ directory.
To start the application in development mode, run:
npm run dev
To build the installer, run:
npm run build
The installer executable will be located in the build/electron folder.
Linux support is experimental. The frontend, AI Backend, LlamaCPP and ComfyUI backends run on Ubuntu x64. The packaged installer/AppImage/.deb supports Ubuntu 24 or newer only. Complete host GPU setup before installing the app — see
docs/linux-intel-gpu-setup.md(Intel OMIX + Vulkan).
The Linux build produces both a single, portable AppImage (no installation, no
root) and a .deb package for a system-wide install via apt.
-
Build it from the
WebUIdirectory:cd WebUI npm install # install build dependencies npm run fetch-external-resources # one-time: downloads uv/7zip npm run build:linux
Both
AI Playground-<version>.AppImageandAI Playground-<version>.debare written tobuild/electron. The build host needsar(frombinutils, usually already present) to assemble the.deb. -
Install FUSE once (required to run any AppImage):
sudo apt install -y libfuse2t64
-
Make it executable and start the app:
cd build/electron chmod +x "AI Playground-"*.AppImage ./"AI Playground-"*.AppImage
--no-sandboxis baked into the launcher (seebuild/scripts/after-pack.cjs), so you can also start the app by double-clicking the AppImage in your file manager — provided the file manager is allowed to run executables (in GNOME Files: Preferences → "Executable Text Files" / right-click → Run, orchmod +xas above). Do not start it withsudo— Electron refuses to run as root.Alternatively, install the
.debinstead of running the AppImage.aptresolves the runtime dependencies declared in the package (libgtk-3-0,libnss3,libasound2,libdbus-1-3,pciutils,python3,git):cd build/electron sudo apt install ./"AI Playground-"*.deb
This installs the app system-wide; launch it as AI Playground from your application menu or run
ai-playgroundfrom a terminal.--no-sandboxis baked into the launcher here too. Uninstall withsudo apt remove ai-playground. -
OpenVINO Ubuntu dependencies are checked during OpenVINO backend setup.
If required packages are missing, AI Playground can open a terminal installer. The terminal asks for your sudo password and runs the package install command.
On Ubuntu, the install command is:
sudo apt-get update sudo apt-get install -y python3 python3-venv libtbb12 libhwloc15 libgomp1 libnuma1 ocl-icd-libopencl1 libfuse2t64
-
ComfyUI Ubuntu build dependencies are checked during ComfyUI backend setup.
ComfyUI is cloned with
gitand some of its Python dependencies (e.g.insightface) are compiled from source during install, which needs a C compiler and the CPython headers. On a fresh Ubuntu these are missing, so AI Playground prompts to install them automatically. To install them manually:sudo apt-get update sudo apt-get install -y git build-essential python3-dev
AI Playground downloads tools at build time (uv, 7zip) and backend binaries
on first run (llama.cpp, OpenVINO/OVMS). Both honor the standard proxy
environment variables when they are set — export them before building or
launching:
export https_proxy="http://proxy.example.com:port"
export http_proxy="http://proxy.example.com:port"
export no_proxy="localhost,127.0.0.1" # hosts to reach directlyWith these set:
- Build (
npm run fetch-external-resources/npm run build:linux) routes Node's downloads through the proxy (the script runs withNODE_USE_ENV_PROXY=1). - Runtime the app reads the same variables at startup and points Electron's
network stack (
net.fetch) at the proxy, so llama.cpp and OVMS downloads succeed.
⚠️ Launching from a file manager won't pick up the proxy. Double-clicking the AppImage starts it from the desktop session, which does not inherithttp_proxyexported in~/.profileor~/.bashrc. Either launch the AppImage from a terminal where the variables are exported, or configure a system-wide proxy (e.g. GNOME Settings → Network → Network Proxy) so the desktop session provides them.
If your network blocks the downloads entirely, you can also pre-place the build
tools manually: drop the extracted uv/7zip binaries into
WebUI/build/resources/ (the fetch script skips any file already present)
before running the build.
A common gotcha on Intel networks: apt and curl honor no_proxy exactly,
but a broad entry like no_proxy=*.intel.com will also match the
externally-hosted CDN repositories.intel.com (resolves to AWS), causing
apt update to hang trying to reach it directly through the corporate firewall.
Work around it by scoping the proxy override per-host rather than rewriting
no_proxy:
# /etc/apt/apt.conf.d/99-intel-proxy
Acquire::http::Proxy::repositories.intel.com "http://proxy.example.com:port";
Acquire::https::Proxy::repositories.intel.com "http://proxy.example.com:port";For interactive curl calls (e.g. fetching the NPU driver tarball from
github.com which redirects to AWS), pass --proxy "$http_proxy" explicitly.
AI Playground does not ship with generative AI models pre-installed. When a task needs a model that is not on disk, the app prompts you to download it (after you accept the model’s terms on the provider site). Use the Model Manager (cylinder icon in the title bar) to browse, search, filter, favorite, download, add Hugging Face paths, and remove models. You can also download models from HuggingFace.co or CivitAI.com and place them in the appropriate model folder.
Models currently linked from the application
| Model Path / Name | Model Card (HF) | License Link |
|---|---|---|
| AdamCodd/vit-base-nsfw-detector | Model Card | Apache 2.0 |
| Aitrepreneur/insightface/inswapper_128.onnx | Model Card | Non-Commercial |
| alimama-creative/FLUX.1-Turbo-Alpha | Model Card | FLUX.1-dev License |
| BGE Small EN v1.5 (GGUF) | Model Card | MIT License |
| black-forest-labs/FLUX.2-klein-4b-fp8/flux-2-klein-4b-fp8.safetensors | Model Card | Apache 2.0 |
| city96/t5-v1_1-xxl-encoder-gguf/t5-v1_1-xxl-encoder-Q3_K_M.gguf | Model Card | Apache 2.0 |
| city96/t5-v1_1-xxl-encoder-gguf/t5-v1_1-xxl-encoder-Q4_K_M.gguf | Model Card | Apache 2.0 |
| city96/umt5-xxl-encoder-gguf/umt5-xxl-encoder-Q4_K_M.gguf | Model Card | Apache 2.0 |
| comfyanonymous/flux_text_encoders/clip_l.safetensors | Model Card | Apache 2.0 |
| comfyanonymous/flux_text_encoders/t5xxl_fp8_e4m3fn_scaled.safetensors | Model Card | Apache 2.0 |
| Comfy-Org/flux1-kontext-dev/flux1-dev-kontext_fp8_scaled.safetensors | Model Card | FLUX.1-dev License |
| Comfy-Org/Lumina_Image_2.0_Repackaged/ae.safetensors | Model Card | Apache 2.0 |
| Comfy-Org/Real-ESRGAN_repackaged/RealESRGAN_x4plus.safetensors | Model Card | BSD-3-Clause |
| Comfy-Org/Wan_2.1_ComfyUI_repackaged/wan_2.1_vae.safetensors | Model Card | Wan 2.1 License |
| Comfy-Org/z_image_turbo/ae.safetensors | Model Card | Apache 2.0 |
| Comfy-Org/z_image_turbo/qwen_3_4b.safetensors | Model Card | Apache 2.0 |
| Comfy-Org/z_image_turbo/z_image_turbo_bf16.safetensors | Model Card | Apache 2.0 |
| DeepSeek-R1-Distill-Qwen 1.5B | Model Card | MIT License |
| DeepSeek-R1-Distill-Qwen 7B | Model Card | MIT License |
| Gemma 3 4B IT (Unsloth) | Model Card | Gemma License |
| gmk123/GFPGAN/GFPGANv1.4.pth | Model Card | Apache 2.0 |
| GPT-OSS 20B (Unsloth) | Model Card | Apache 2.0 |
| InternVL2 4B (OV) | Model Card | Apache 2.0 |
| latent-consistency/lcm-lora-sdv1-5/pytorch_lora_weights.safetensors | Model Card | OpenRAIL++ |
| latent-consistency/lcm-lora-sdxl/pytorch_lora_weights.safetensors | Model Card | OpenRAIL++ |
| Lightricks/LTX-Video/ltxv-2b-0.9.6-distilled-04-25.safetensors | Model Card | Apache 2.0 |
| Llama 3.2 3B Instruct | Model Card | Llama 3.2 License |
| lllyasviel/fooocus_inpaint/fooocus_inpaint_head.pth | Model Card | OpenRAIL |
| lllyasviel/fooocus_inpaint/inpaint_v26.fooocus.patch | Model Card | OpenRAIL |
| Lykon/DreamShaper/DreamShaper_8_pruned.safetensors | Model Card | OpenRAIL-M |
| Lykon/dreamshaper-8-inpainting/text_encoder/model.safetensors | Model Card | OpenRAIL-M |
| Lykon/dreamshaper-8-inpainting/unet/model.safetensors | Model Card | OpenRAIL-M |
| Lykon/dreamshaper-8-inpainting/vae/model.safetensors | Model Card | OpenRAIL-M |
| Meta-Llama 3.1 8B Instruct | Model Card | Llama 3.1 License |
| Mistral 7B Instruct v0.2 (OV) | Model Card | Apache 2.0 |
| Mistral 7B Instruct v0.3 | Model Card | Apache 2.0 |
| Mistral 7B Instruct v0.3 (OV) | Model Card | Apache 2.0 |
| Nomic Embed Text v1.5 (GGUF) | Model Card | Apache 2.0 |
| Phi-3 Mini 4k Instruct (OV) | Model Card | MIT License |
| Phi-3.5 Mini Instruct (OV) | Model Card | MIT License |
| QuantStack/Wan2.1_14B_VACE-GGUF/Wan2.1_14B_VACE-Q8_0.gguf | Model Card | Apache 2.0 |
| Qwen2-VL 7B Instruct (OV) | Model Card | Apache 2.0 |
| Qwen3 4B (OV) | Model Card | Apache 2.0 |
| Qwen3 4B (Unsloth) | Model Card | Apache 2.0 |
| Qwen3 4B Instruct 2507 (Unsloth) | Model Card | Apache 2.0 |
| Qwen3-VL 4B Instruct (Unsloth) | Model Card | Apache 2.0 |
| RunDiffusion/Juggernaut-XL-v9/RunDiffusionPhoto_v2.safetensors | Model Card | OpenRAIL-M |
| SmolLM2 1.7B Instruct | Model Card | Apache 2.0 |
| stabilityai/control-lora/rank128-canny-rank128.safetensors | Model Card | SAI Community |
| tencent/Hunyuan3D-2.1/hunyuan3d-dit-v2-1/model.fp16.ckpt | Model Card | Hunyuan3D License |
| tencent/Hunyuan3D-2/hunyuan3d-dit-v2-0/model.fp16.safetensors | Model Card | Hunyuan3D License |
| TinyLlama 1.1B Chat (OV) | Model Card | Apache 2.0 |
| Whisper (OV) | Model Card | Apache 2.0 |
Be sure to check license terms for any model used in AI Playground especially taking note of any restrictions.
Check the User Guide for details or watch this video on how to add alternative Stable Diffusion models to AI Playground
For information on AI Playground terms, license and disclaimers, visit the project and files on GitHub repo:
License | Notices & Disclaimers
The software may include third party components with separate legal notices or governed by other agreements, as may be described in the Third Party Notices file accompanying the software.
License details for borrowed code and components can be found in our 3rdpartynoticeslicense file.
Additionally, these entities and their work stand out as are fundamental to AI Playground.
- PyTorch - https://pytorch.org/
- Stable Diffusion - https://github.com/Stability-AI/stablediffusion
- ComfyUI - https://github.com/comfyanonymous/ComfyUI
- OpenVINO - https://openvinotoolkit.github.io/openvino.genai/
- Llama.cpp - https://github.com/ggml-org/llama.cpp
- Vue.js - https://vuejs.org/
- Plus countless other open-source projects and contributors that make this work possible!




