Local AI Models: Why Local Instead of Cloud?
Learn why more and more users are running AI models locally on their own PCs and what advantages this brings.
Table of Contents
01What Are Local AI Models?
Local AI models are artificial intelligence systems that run directly on your own computer, rather than through cloud services like OpenAI, Midjourney, or Google. They use your GPU and CPU computing power to generate images, videos, text, and more – completely offline and without an internet connection.
02Advantages of Local AI
There are numerous reasons to run AI models locally:
- Privacy & Data Protection: Your data never leaves your computer. No prompts, images, or personal information is sent to external servers.
- No Ongoing Costs: After the one-time hardware investment, there are no monthly subscription fees or API costs.
- Full Control: You decide which model to use, how to configure it, and which parameters to set. No censorship or restrictions from providers.
- Offline Usage: Once models are downloaded, everything works without an internet connection – ideal for on-the-go or sensitive environments.
- Unlimited Usage: No rate limits, no queues, no 'fair use' restrictions. Generate as much as you want.
- Customizability: Train your own LoRAs, combine models, and create individual workflows tailored exactly to your needs.
03Disadvantages and Challenges
To be fair, there are also challenges with local usage:
- Hardware Requirements: You need a powerful GPU with sufficient VRAM – especially for large models.
- Setup Effort: Installation and configuration can be technically demanding, especially for beginners.
- Model Updates: You need to manually download and update models, while cloud services automatically provide the latest versions.
- Power Consumption: GPU-intensive computations can increase your electricity bill, especially during prolonged operation.
04When Is Local Usage Worth It?
Local AI is especially worthwhile if you regularly generate AI content, value data privacy, or need specific customizations. For occasional users, a cloud service may be simpler initially. Many users start with cloud services and then switch to local solutions once they recognize the benefits and flexibility.
05Getting Started
To get started with local AI, you essentially need three things: A compatible GPU (NVIDIA recommended), software like ComfyUI or Stable Diffusion WebUI, and the corresponding model files. In our further articles, we go into each of these points in detail.
Hardware Recommendations
The best hardware for local AI generation. Our recommendations based on price-performance and compatibility.
Graphics Cards (GPU)
NVIDIA RTX 3060 12GB
EntryBest entry-level model for local AI. 12 GB VRAM is sufficient for SDXL and small LLMs.
from ~$300NVIDIA RTX 4070 Ti Super 16GB
RecommendedIdeal mid-range GPU. 16 GB VRAM for Flux, SDXL, and medium-sized LLMs.
from ~$800NVIDIA RTX 4090 24GB
High-EndHigh-end GPU for demanding models. 24 GB VRAM for Wan 2.2 14B and large LLMs.
from ~$1,800NVIDIA RTX 5090 32GB
EnthusiastMaximum performance and VRAM. 32 GB for all current and future AI models.
from ~$2,200* Affiliate links: If you purchase through these links, we receive a small commission at no additional cost to you. This helps us keep ComfyVault free.
No GPU? Rent Cloud GPUs
You don't need to buy an expensive GPU. Cloud GPU providers allow you to run AI models on powerful hardware by the hour.
RunPod
PopularCloud GPUs from $0.20/hr. Ideal for testing large models without expensive hardware. Easy ComfyUI templates available.
from $0.20/hrVast.ai
BudgetCheapest cloud GPUs on the market. Marketplace model with GPUs from $0.10/hr. Perfect for longer training sessions.
from $0.10/hrLambda Cloud
PremiumPremium cloud GPUs with A100/H100. For professional users who need maximum performance.
from $1.10/hr* Affiliate links: If you sign up through these links, we receive a small commission. There are no additional costs for you.