🌐 Links
📋 Requirements
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Node.js and Python 3.11 must be installed.
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Optional Wan2GP video service: needs a few extra GB of disk space and the CUDA/driver version matching your GPU generation (exact requirements are shown in the setup confirmation window).
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LLM-Runner-AIO.exe handles the automatic setup.
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After extracting the LLM-Runner-AIO.rar files, you must run run.bat first; this script installs the necessary dependencies, configures Pi Coding settings, and creates a desktop shortcut.
📦 What Does the Application Include?
Searxng and llama.cpp server settings are pre-configured. You can also load functions found in the folder if you wish (e.g., EasySearch, Export to PDF/Excel/DOCX, unload llama.cpp, thinking toggle, pp/tg metrics).
llama.cpp (Pre-compiled CUDA 13 + Vulkan versions) link: https://github.com/ggml-org/llama.cpp
These are the versions I have configured (every model below ships with chat, vision and coding profiles):
gpu1vram10ram32models.ini, gpu1vram12ram32models.ini, gpu1vram16ram32models.ini
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qwen3.6-35B-A3B
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gemma-4-26B
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qwen3.8-27B
gpu1vram8ram32models.ini
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qwen3.6-35B-A3B
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gemma-4-26B
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gemma-4-E4B
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qwen3.8-27B
gpu1vram4ram32models.ini, gpu1vram6ram32models.ini
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qwen3.6-35B-A3B
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gemma-4-26B
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gemma-4-E4B
gpu1vram24ram32models.ini
gpu1vram32ram32models.ini
gpu1vram4ram16models.ini
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gemma-4-E4B
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qwen3.5-4B
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Ling-3.0-tiny
gpu1vram6ram16models.ini
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gemma-4-E4B
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qwen3.5-9B
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Ling-3.0-tiny
All of the model lists above can be managed directly from the GUI — no manual INI editing needed (see “GUI Model Manager” in Key Features).
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SearXNG (Completely private local web search) link:
https://github.com/searxng/searxng
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Pi Coding (Pi is a minimal agent harness) link:
https://github.com/earendil-works/pi
Web search and Advisor (use your own API key) pre-installed.
- Vane Search (For web search) link: https://github.com/ItzCrazyKns/Vane
llama.cpp and searxng settings pre-configured.
- Wan2GP (AI image/video generation, runs locally) link: https://github.com/deepbeepmeep/Wan2GP
Optional integrated service. Press "Setup" in the Wan2GP card (System tab): the app clones the repository, builds a dedicated virtual environment (venvs/wan2gp) and installs the package set matching your GPU generation — without touching the rest of the app.
🚀 Key Features:
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No Manual Installation Required: It is a single 2 GB .exe file. Simply double-click and wait for the installation to complete. It automatically installs Python, Node, and all necessary dependencies within a local virtual environment (venv).
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Automatic Hardware Detection: The application automatically detects your GPU/VRAM and configures your system according to a specific hardware profile (VRAM options: 4GB, 6GB, 8GB, 12GB, 16GB, 24GB, and 32GB). * Smart Model Downloader: Simply select an auto-detection profile and click the model download button. The application filters and downloads models that perfectly match your VRAM capacity and configures llama.cpp accordingly.
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GUI Model Manager: Add, edit, or remove models straight from the System tab. The app rewrites the active preset INI safely (comments and order preserved), keeps the corresponding download URLs in sync in model_urls.json, and offers one-click URL health checks for a single model or for every model at once.
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Built-in Video Generation (Wan2GP): The app detects your GPU generation, picks the right package (NVIDIA GTX 10xx – RTX 50xx, AMD RX 6xxx / 7xxx / 9xxx / APU, Intel Arc), and lets you install, start, stop and monitor the Wan2GP server from the same screen. Port and network binding are configurable (default port: 7860).
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Optimized for Coding Agents: Includes parameters fine-tuned specifically for Qwen and Gemma models to maximize token speed and eliminate formatting or context loop issues in coding tools.
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100% Open Source: You can review the entire source code on the website.
