Pinokio: The One-Click AI App Store for Your PC 🚀
Setting up AI tools on your own computer can be a headache — installing Python, managing dependencies, downloading model files, configuring CUDA. Enter Pinokio. It's like an app store for AI software — you browse, click install, and it handles everything in the background. No terminal commands, no dependency hell. Just one click and you're running advanced AI tools locally.
Pinokio is a free open-source AI desktop app (MIT license) by the creator of pinokio.computer — an AI launcher that wraps complex open-source projects into one-click install scripts. Think of it as an AI app store — the best way to discover best AI apps for your PC. You browse an AI app directory, hit install, and Pinokio downloads dependencies, sets up virtual environments, and configures everything in an isolated folder at ~/pinokio. Nothing touches your system. Total size of Pinokio itself is ~200MB.
Unlike Ollama (see our Pinokio vs Ollama comparison below) which only runs LLMs, Pinokio installs everything — image generators like FLUX, video generators like CogVideo and Wan, AI voice cloning and TTS voice clone tools, background removers, 3D model generators, and even coding AI agents. It has 100+ AI applications in its directory — making it the best way to install AI tools locally. And it works on any desktop platform.
In this Pinokio tutorial for 2025, let's look at the top Pinokio models and apps and how to get started. Which tools are worth installing, what hardware do you need, and — most importantly — how to run AI locally without headaches. 🔍
🏆 Top Downloaded Apps on Pinokio
🥇 CogStudio — ⭐ 392 stars — 🎬 Best video generation suite
A powerful Gradio web UI for CogVideo (by Tsinghua / Zhipu AI). Supports text-to-video, video-to-video, image-to-video, and extend-video (make videos longer frame by frame). Has a seamless tab-based workflow — generate a video, then send it to video-to-video or extend with one click. NVIDIA GPU required.
💾 VRAM: 8GB+ (NVIDIA GPU required)
⚙️ Hardware: Consumer GPUs with 8GB+ VRAM (RTX 3070/4070). For high-res or long videos, latest high-end GPUs with 24GB+ VRAM are recommended.
🥈 RMBG-2 Studio — ⭐ 249 stars — 🖼️ Best background removal app
Enhanced image background removal and replacement tool built around BRIA-RMBG-2.0. Removes backgrounds from any image with one click, supports replacement with custom backgrounds, and runs efficiently even on low-end hardware. One of the few AI tools that works without a powerful GPU.
💾 VRAM: ~2-4GB (integrated GPU or low-end GPU works)
⚙️ Hardware: Runs on modern CPUs and entry-level consumer GPUs. ~6GB total install size. Perfect for laptops and older machines.
🥉 FLUX WebUI — ⭐ 188 stars — 🖌️ Best image generation UI
A minimal Gradio web UI for Black Forest Labs' FLUX.1 models — FLUX.1-schnell (fast, 4-step inference) and FLUX.1-merged (dev quality in 8 steps). Automatically downloads checkpoints from HuggingFace so everything just works. Minimal, no-nonsense interface for text-to-image generation.
💾 VRAM: ~6-8GB (FLUX.1-schnell), ~10-12GB (FLUX.1-merged)
⚙️ Hardware: Requires consumer GPUs with 8GB+ VRAM (RTX 3070/4080). macOS MPS supported via Apple Silicon — runs on M1/M2/M3 Macs with 16GB+ unified memory.
4️⃣ e2-f5-tts — ⭐ 80 stars — 🔊 Best TTS voice cloning
Powers E2 TTS and F5-TTS — two state-of-the-art zero-shot text-to-speech models that can clone any voice from a short audio sample. Generate natural speech with emotional variation, pacing control, and speaker similarity. One of the best open-source TTS options available.
💾 VRAM: ~4-6GB
⚙️ Hardware: Runs on consumer GPUs with 6GB+ VRAM. Also works on modern CPUs at slower speeds. macOS MPS support available.
5️⃣ Bolt — ⭐ 59 stars — 💻 AI coding assistant
A local AI coding agent similar to Claude Code or Cursor. Write prompts and Bolt generates code, runs it, and debugs it — all within Pinokio. Uses local models or connects to cloud APIs. Think of it as a local ChatGPT for programming.
💾 VRAM: Depends on model — Ollama models from 4-24GB
⚙️ Hardware: Small models run on modern CPUs or any consumer GPU. Larger local models need latest high-end GPUs (RTX 4090/5090). Can also use cloud APIs with no local GPU needed.
6️⃣ Clarity Refiners UI — ⭐ 52 stars — ✨ Best image upscaler & enhancer
Creative image enhancer and upscaler powered by Refiners. Takes low-res or blurry images and makes them crisp and detailed. Supports batch processing for multiple images. Great for restoring old photos or upscaling AI-generated images.
💾 VRAM: ~6-8GB
⚙️ Hardware: Runs on consumer GPUs with 8GB+ VRAM. ~10GB total install size.
7️⃣ Wan — ⭐ 36 stars — 🎥 Alibaba's video generator
Pinokio launcher for Alibaba's Wan2.2 video generation model — the state-of-the-art open-source text-to-video model. Generates impressive videos from text prompts. Works with NVIDIA GPUs and has a clean web interface.
💾 VRAM: ~12-16GB
⚙️ Hardware: Requires latest high-end GPUs with 16GB+ VRAM (RTX 4090/5090). Not for consumer-grade mid-range GPUs.
8️⃣ OpenAudio — ⭐ 27 stars — 🎵 Audio generation & editing
Open-source audio generation tool. Create music, sound effects, and voice content from text prompts. Supports text-to-audio and audio-to-audio transformations. Built for creative professionals who want AI-powered audio without cloud subscriptions.
💾 VRAM: ~4-8GB depending on model
⚙️ Hardware: Runs on consumer GPUs with 6GB+ VRAM. Smaller models work on modern CPUs.
9️⃣ ComfyUI (Pinokio script) — ⭐ 25 stars — 🧩 Node-based AI workflow builder
Pinokio launcher for ComfyUI — the popular node-based interface for Stable Diffusion and image generation workflows. Connect nodes visually to create complex pipelines: image generation, upscaling, inpainting, video frame processing. The most flexible AI image tool available.
💾 VRAM: ~4-8GB (depending on models)
⚙️ Hardware: Consumer GPUs with 6GB+ VRAM (RTX 3060/4060 and up). For SDXL/FLUX workflows, latest high-end GPUs recommended.
🔟 MFLUX WebUI — ⭐ 23 stars — ⚡ Hyper-fast FLUX interface
A powerful Gradio web interface for MFLUX — a distilled version of FLUX that's faster while maintaining quality. Built on Gradio with an intuitive UI. Great for quick image generation without heavy resource usage.
💾 VRAM: ~4-6GB
⚙️ Hardware: Runs on consumer GPUs with 6GB+ VRAM. More efficient than standard FLUX.
🎖️ Honourable mentions
🎬 FramePack — ⭐ 21 stars
Created by Lvmin Zhang (the mind behind ControlNet and Fooocus), FramePack is a next-frame prediction neural network that generates video sequences from a starting frame. Built on the HunyuanVideo diffusion architecture, it's designed for image-to-video generation with ~3.3B parameters in the transformer. Runs well on consumer GPUs and is perfect for creating smooth video transitions from still images. CPU only not supported — requires an NVIDIA GPU.
💾 VRAM: ~6-8GB (NVIDIA GPU required)
⚙️ Hardware: Runs on consumer GPUs with 8GB+ VRAM. Latest high-end GPUs recommended for higher resolution or longer sequences.
🎥 HunyuanVideo — ⭐ 18 stars
Tencent's open-source text-to-video generation model, now available as a one-click Pinokio app. Generates impressive videos from text descriptions with decent quality and motion coherence. Supports various resolutions and aspect ratios. One of the more accessible video generation models for local use. CPU only not supported — NVIDIA GPU required.
💾 VRAM: ~12-16GB
⚙️ Hardware: Requires latest high-end GPUs with 16GB+ VRAM (RTX 4090/5090). Not suitable for mid-range consumer GPUs.
💬 OpenUI — ⭐ 19 stars
An AI-powered tool that generates UI components and web interfaces from text prompts. Describe what you want — a login form, a dashboard, a settings page — and OpenUI generates the HTML/CSS code instantly. Perfect for frontend prototyping and designers who want to go from idea to code fast. Runs on any hardware.
💾 VRAM: Minimal — runs as a web app, uses API calls to an LLM backend
⚙️ Hardware: Runs on any modern CPU. No GPU needed.
🎁 Other notable mentions
DiffRhythm (⭐ 19) — generate full songs with lyrics
FacePoke (⭐ 18) — AI face editing and expression control
TRELLIS (⭐ 18) — Microsoft's 3D asset generator
StyleTTS2 Studio (⭐ 12) — build your own custom TTS voice
💾 Hardware Requirements at a Glance
🖥️ Modern CPUs (no GPU needed)
Apps that work on CPU: RMBG-2 Studio (background removal), StyleTTS2, some TTS tools. Image/video generation apps require a GPU — no exceptions for diffusion models.
🕰️ Old Consumer GPUs (4-6GB VRAM)
Examples: GTX 1050/1060/1070/1080, GTX 1650/1660, RTX 3050, AMD RX 480/580/590 (roughly any GPU from the GTX 1000 series onwards)
Can run: RMBG-2 (any GPU), ComfyUI with SD1.5/FLUX-schnell at lower resolution, e2-f5-tts, MFLUX WebUI, FramePack at reduced quality, OpenAudio, FacePoke, StyleTTS2
These older cards are still usable for lighter AI workloads. Expect lower resolution outputs and slower generation speeds — a GTX 1060 takes ~30-60 seconds per FLUX image. Still perfectly fine for background removal, TTS, and basic image workflows.
🎮 Consumer GPUs (8-16GB VRAM)
Examples: RTX 3060/3070/4060/4070/4080, AMD RX 7000 series
Can run: CogStudio (8GB+), RMBG-2 (any GPU), FLUX WebUI (8GB+), e2-f5-tts, Clarity Refiners, ComfyUI, MFLUX, FramePack, OpenAudio, DiffRhythm, FacePoke, StyleTTS2
🚀 Latest High-End GPUs (24GB+ VRAM)
Examples: RTX 4090/5090, A6000, A100
Can run: Wan video gen (16GB+), CogStudio (high-res), FLUX with high-res outputs, HunyuanVideo, TRELLIS 3D, all apps at higher quality/precision
macOS users: Apple Silicon Macs (M1-M4) with 16GB+ unified memory can run MPS-accelerated apps like FLUX WebUI, e2-f5-tts, and basic ComfyUI workflows. Higher-end models still need NVIDIA GPUs.
📦 How to Install Pinokio (All Platforms)
🪟 Windows
Go to pinokio.computer and click Download. Choose the Windows 64-bit installer. Run the .exe file — it installs like any Windows app. Open Pinokio, browse the Discover page, and click "Install" on any app. That's it. Pinokio handles Python, conda environments, CUDA toolkit setup, and dependency installation automatically inside its sandbox folder.
🍎 macOS
Download from pinokio.computer. Choose Apple Silicon (for M1/M2/M3/M4 Macs) or Intel (for older Intel Macs). The download is a .dmg file — open it and drag Pinokio to Applications. Launch it. Apps that support MPS acceleration (like FLUX WebUI, ComfyUI, e2-f5-tts) will use your Mac's GPU automatically. Install size: ~200MB for Pinokio itself, plus 2-10GB per installed app.
🐧 Linux
Download options from pinokio.computer/release include:
• AppImage — universal, works on any distro: chmod +x Pinokio*.AppImage && ./Pinokio*.AppImage
• .deb — for Debian/Ubuntu: sudo dpkg -i pinokio*.deb
• .rpm — for Fedora/RHEL: sudo rpm -i pinokio*.rpm
• ARM64 versions available for Raspberry Pi 5 and other ARM Linux devices
First launch may take a moment as it initializes its environment. All installed apps go inside ~/pinokio/api/.
🤖 Android
Pinokio has no official Android version. However, you can run a Pinokio server mode on your desktop and access the web UI remotely from your phone browser. For actual on-device AI, use Termux with lightweight models — but Pinokio itself is desktop-only.
🐳 Docker
Pinokio doesn't have an official Docker image. But since each app in Pinokio runs in its own isolated environment (conda/env), it's already containerized by design. For a Docker setup of individual apps, each Pinokio launcher script references the original project's Docker instructions.
🎯 How to Use Pinokio
Using Pinokio is simpler than most AI tools:
1️⃣ Install Pinokio from pinokio.computer
2️⃣ Open the Discover page to browse available apps
3️⃣ Click Install on any app — Pinokio downloads and configures everything
4️⃣ Launch the app — each app opens in its own browser tab with a web UI
5️⃣ Use it — generate images, videos, audio, or code right in your browser
Each installed app runs on a localhost port (e.g., http://localhost:7860). Pinokio handles starting, stopping, and updating each app. You can install multiple versions of the same app and switch between them.
🔄 Pinokio vs Alternatives
Pinokio is unique — it's an AI software installer, not a model runner. It's the one open-source AI tools manager that bridges the gap between "too complicated to set up" and "need it running now." Here's how it compares:
• Ollama — runs LLMs locally via CLI. Pinokio installs anything — LLMs, image gen, video gen, TTS, coding agents. They complement each other: you can install Ollama via Pinokio!
• LM Studio — GUI for running GGUF models. More polished for chat, but limited to LLMs only. Pinokio covers a much wider range of AI tools.
• ComfyUI — node-based workflow builder for image/video. Can be installed through Pinokio as a one-click app.
• Stable Diffusion WebUI (AUTOMATIC1111) — popular image generation UI. Also installable via Pinokio.
• Docker — Pinokio fills a similar "app packaging" role but is much simpler for non-technical users. No Dockerfile needed, no compose files.
Think of Pinokio as the App Store for AI tools on desktop — it doesn't replace any single tool, it makes installing and running ALL of them easier. Like having an AI software installer that handles every app for you.
🔮 Is Pinokio Right for You?
If you're tired of copy-pasting terminal commands, troubleshooting Python dependency conflicts, and manually downloading model checkpoints for local image generation — Pinokio is for you. It's perfect for beginners who want to experiment with local AI applications without the technical overhead, and for experts who want a clean, organized way to manage multiple AI tools without polluting their main system.
Since it installs everything in ~/pinokio, your system stays clean. Uninstalling an app is one click. Want to try video generation without the setup nightmare? Install CogStudio via Pinokio. Want to clone voices? Install e2-f5-tts. Everything just works. 🚀
🤝 Alternatives to Pinokio
• Ollama — best for running LLMs locally via CLI. Lightweight, fast, but limited to text models only.
• LM Studio — polished GUI for GGUF chat models. Great for beginners, but LLM-only.
• ComfyUI — node-based AI image/video pipeline. Extremely flexible but steeper learning curve.
• Stable Diffusion WebUI (Forge) — image generation focused. More features than Pinokio's FLUX WebUI but manual setup.
• LocalAI — Docker-based local AI server. Good for API integration but less beginner-friendly.
• Docker Compose — manual setup for any AI tool. Most control but highest setup effort.