# AI Computer Guide

> Expert hardware validation for local AI inference. Focused on providing VRAM-centric logic for building, predicting, and comparing computers optimized for running large language models locally.

## Full AI Data Protocol
We provide a massive, complete machine-readable dataset outlining every GPUs specifications including VRAM, bandwidth, and AI Tops. We also include our entire guide text corpus for direct NLP ingestion.
- [Full Machine-Readable Knowledge Base](https://aicomputerguide.com/llms-full.txt)

## Core Utilities & Hardware Matrix
- [Will It Run? Validator](https://aicomputerguide.com/tools/will-it-run)
- [AI PC Builder](https://aicomputerguide.com/builder)
- [Hardware Directory (All GPUs & Macs)](https://aicomputerguide.com/hardware)
- [Ollama Prompts & Personas](https://aicomputerguide.com/ollama-prompts)

## Knowledge Base & Setup Guides
- [Host Small Business AI Locally: Replace Monthly Cloud Subscriptions](https://aicomputerguide.com/articles/local-ai-small-business-replace-subscriptions): A comprehensive guide for small businesses to replace expensive cloud AI subscriptions with a single localized mini PC setup running open-source models like Qwen and Llama.
- [Best Local AI Coding Models of 2026: VRAM Tiers and Benchmarks](https://aicomputerguide.com/articles/best-local-coding-models-2026): The definitive guide to the best local AI coding models in 2026. Ranked by VRAM requirements, hardware needs, benchmarks, and editor setup. Replace GitHub Copilot with privacy.
- [Best Budget GPU for AI in 2026: Under $300, $400, and $500 Picks](https://aicomputerguide.com/articles/best-budget-gpu-ai-2026): The best budget GPUs for running local AI in 2026, organized by price tier. Top picks for under $300, $400, and $500 with real benchmarks, VRAM analysis, and model compatibility.
- [How Much VRAM Do You Need to Run LLMs in 2026? The Complete Guide](https://aicomputerguide.com/articles/how-much-vram-for-llm-2026): The definitive VRAM guide for running local LLMs in 2026. Model-by-model VRAM requirements, quantization explained, and GPU recommendations for every budget.
- [Best GPU for Local AI & LLMs in 2026](https://aicomputerguide.com/articles/best-gpu-local-ai-llms-2026): The best GPUs for running local LLMs in 2026, ranked by budget. VRAM requirements, tokens/sec benchmarks, model compatibility, and affiliate links for every tier.
- [RTX 4090 vs RTX 3090 for Local LLMs — Which Should You Buy in 2026?](https://aicomputerguide.com/articles/rtx-4090-vs-rtx-3090-for-ai): RTX 4090 vs RTX 3090 for local LLMs: head-to-head benchmarks, VRAM analysis, price comparison, and a clear verdict on which 24GB GPU is worth your money in 2026.
- [Best GPU for DeepSeek R1: The Ultimate VRAM Guide](https://aicomputerguide.com/articles/best-gpu-for-deepseek-r1): DeepSeek R1 requires massive VRAM for native inference. Learn how quantization, FP8 precision, and CUDA cores impact performance.
- [Llama 3.3 Hardware Requirements: What You Actually Need](https://aicomputerguide.com/articles/llama-3-3-hardware-requirements): Everything you need to know about running Llama 3.3 locally, from VRAM capacity to system memory overhead.
- [Stable Diffusion XL: Does VRAM Capacity Affect Speed?](https://aicomputerguide.com/articles/stable-diffusion-xl-vram-vs-speed): In image generation, VRAM affects batch size and resolution. We compare RTX 4090 vs RTX 5080.
- [Fine-tuning 8B Models on a Budget: 16GB is the Key](https://aicomputerguide.com/articles/fine-tuning-8b-models-on-a-budget): Learn why the AMD RX 9070 and RTX 5070 Ti are great for entry-level model fine-tuning.
- [NVIDIA RTX 5090 Blackwell: The New AI Standard](https://aicomputerguide.com/articles/rtx-5090-blackwell-ai-benchmark): The RTX 5090 is officially here. We break down its performance for local LLM inference and training.
- [Mastering QLoRA for 8B Models: Efficiency Guide](https://aicomputerguide.com/articles/mastering-qlora-for-8b-models): Learn the exact VRAM requirements and hyperparameter settings for QLoRA fine-tuning on Llama 3 8B.
- [Unsloth: The 2x AI Training Speedup Tutorial](https://aicomputerguide.com/articles/unsloth-2x-training-speedup): Unsloth is taking the local AI world by storm. Discover how to reduce VRAM by 70% and double your training speed.
- [Full Fine-Tuning vs PEFT: The VRAM Reality Check](https://aicomputerguide.com/articles/full-fine-tuning-vs-peft-vram): Do you need an A100 or an RTX 4090? We compare the VRAM cost of all fine-tuning methods.
- [Dataset Quality: Better Models with Fewer Tokens](https://aicomputerguide.com/articles/dataset-quality-for-fine-tuning): Why 1,000 high-quality tokens beat 50k noisy ones for specialized task fine-tuning.