Your definitive resource for running AI models on your own hardware.Learn, explore, and implement with complete privacy and control.
Discover the revolutionary advantages of running Large Language Models on your own hardware
Keep your data completely private. No cloud dependencies, no data sharing, complete control over your AI interactions.
No subscription fees or per-token charges. One-time hardware investment for unlimited AI usage.
Customize models, fine-tune for your needs, and experiment freely without limitations or restrictions.
Calculate requirements, compare models, and make informed decisions with our interactive tools
Calculate memory requirements
Determine exactly how much VRAM you need for different model sizes and configurations. Get precise calculations for optimal performance.
Compare performance metrics
Compare different LLM models side-by-side. Analyze performance, memory usage, and capabilities to find the perfect model for your needs.
Stay ahead with cutting-edge guides, tutorials, and insights about Local LLMs
Get instant answers to the most common questions about Local LLMs
A Local LLM operates natively on your hardware, ensuring your sensitive data stays private. It eliminates cloud latency, removes monthly costs, and gives you total control to customize the AI for your specific needs.
For standard 8B models (like Llama 3.1), you need 6-8GB VRAM. Mid-range 14B models (like Qwen3) require 10-12GB. High-performance 32B models demand 24GB VRAM, while workstation-class 70B models need 46GB+ or dual-GPU setups.
Start with Llama 3.1 8B if you have 8GB VRAM—it's the new standard. For 12GB+ cards, upgrade to Qwen 3 14B or Mistral Nemo for smarter responses. Low-power laptops runs Llama 3.2 3B well. For enthusiasts on edge devices, lightweight models like Qwen3 (0.6B-4B) and Gemma 3 (270M-4B) are the perfect starting point.
Join thousands of developers and AI enthusiasts who have taken control of their AI infrastructure.Start building the future of private AI today.
