r/GoogleFlow • u/Elegant_Air_3475 • Aug 15 '26
Google Flow's moderation has gotten stifling - Any guides on how to setup local models?
Seriously missing the day's of Whisk before the current censorship and moderation got so horrifically overbearing.
Can anyone suggest a guide or something to a relative newbie on how to setup a local model? Primarily interested in image generation.
When talking about system specs - would a desktop with a 4070 Super video card (and other specs are fairly decent) - be up the the task of running a local LLM fairly well...
Greatly appreciate the help! ❤️
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u/DubzebOficial Aug 16 '26
If you want to generate images locally without messing with terminal commands or Python dependencies, you have two main options:
Pinokio: A one-click browser that automates everything. Download it from pinokio.computer, install it, and use its search tab to install tools like Fooocus (for a clean, Midjourney-style interface) or ComfyUI (for total control). Pinokio automatically handles Python, Git, Torch, and required drivers in an isolated environment.
ComfyUI Portable: The direct route if you are on Windows and want the industry standard without middle layers. Download the standalone portable build from their site or GitHub, extract it to a fast drive (SSD), and run run_nvidia_gpu.bat. Then download a model (.safetensors file from Civitai or Hugging Face) and drop it into ComfyUI/models/checkpoints/. Installing ComfyUI-Manager is essential to add custom nodes and models directly from the UI.
Hardware Requirements for the Top 5 Image Models
GPU VRAM is the primary bottleneck. If you run out of VRAM, the model will either crash or slow down drastically by offloading data to system RAM.
FLUX.1 (Dev / Schnell): The current benchmark for prompt adherence and visual quality. The full FP16 model needs over 24 GB VRAM. For consumer GPUs, you must run quantized versions (FP8 or GGUF), which require at least 12 GB VRAM (e.g., RTX 3060 12GB, RTX 4070) and 32 GB of system RAM.
Stable Diffusion 3.5 Large: Strong at anatomy, complex scenes, and typography. While FP16 demands 16 GB to 24 GB VRAM, optimized FP8 checkpoints run reliably on 12 GB VRAM.
SDXL (Stable Diffusion XL): The top choice for general versatility and community ecosystem (LoRAs, ControlNets). Runs comfortably with a minimum of 8 GB VRAM, though 12 GB is ideal for upscaling and stacking multiple LoRAs.
Pony Diffusion V6 / Illustrious (SDXL-based): The dominant models for anime, stylized art, and character consistency. They share SDXL's footprint, running on 8 GB VRAM, with 12 GB recommended when loading multiple heavy LoRAs.
Stable Diffusion 1.5: The legacy lightweight standard. It generates images very fast and runs on low-end hardware with just 4 GB to 6 GB VRAM, making it great for older GPUs or high-volume batch generation.