Guides & Tutorials
Everything you need to know about running LLMs locally, from VRAM calculations to step-by-step setup.
VRAM Guides
How Much VRAM Does Llama 3 Need? Complete Guide
Find out exactly how much VRAM you need to run Llama 3 models locally, from the 8B variant on a budget GPU to the full 405B on multi-GPU setups.
July 30, 2026Best LLMs You Can Run on 8 GB VRAM (2026)
Eight gigabytes of VRAM is tight but far from useless. Here are the best models that actually fit, with honest trade-offs and practical setup advice.
July 30, 2026Best LLMs for 16 GB VRAM GPUs (2026)
Sixteen gigabytes of VRAM is the sweet spot for local LLM inference in 2026. Here are the models that make the most of it across coding, reasoning, and general use.
July 30, 2026Best LLMs for 6 GB VRAM (2026)
Only ~5.5GB is actually usable after OS overhead. Here are the models that genuinely fit, and the context length trade-offs you need to make.
July 30, 2026Best LLMs for 12 GB VRAM (2026)
12 GB unlocks 14B dense models at Q4 and MoE models via CPU offloading. Here is what actually fits, with real benchmark data from the community.
July 30, 2026Best LLMs for 24 GB VRAM (2026)
24 GB unlocks the 32B parameter class at Q4. The '70B at Q2 vs 32B at Q4' debate divides the community. Here is what the data says.
July 30, 2026Best LLMs for 48 GB VRAM (2026)
48 GB is where 70B models become practical daily drivers, or you can run a smaller 2026 model at Q8 instead. Here is everything about multi-GPU setups, long context, and the best models for this tier.
July 30, 2026Llama Family Guide: Llama 3 to Llama 4 (VRAM & Hardware)
From Llama 3.1 8B to the 400B MoE Maverick: here is exactly how much VRAM each Llama model needs, and the critical MoE nuance most guides get wrong.
July 30, 2026Qwen Family Guide: 2.5 to 3.6
Qwen 3.6-27B ties Claude Sonnet 4.5 on coding and fits on a single 24 GB GPU. Here is the complete Qwen family breakdown.
July 30, 2026DeepSeek Family Guide: R1, V3 & Distilled Models
DeepSeek R1 is 671B MoE, but the distilled 14B scores 69.7% on AIME and fits on a $200 GPU. Here is the complete breakdown.
July 30, 2026Mistral & Mixtral Family: Complete VRAM Reference
Mistral Large 2 was API-only: Mistral Large 3 (675B MoE) isn't. Mixtral 8x7B Q4 needs 28 GB, just past the RTX 4090. Here is the complete Mistral ecosystem.
July 30, 2026Hardware
Best GPU for Running LLMs Locally in 2026
Buying a GPU for local LLMs? VRAM matters more than compute. Here is a practical buyer's guide covering every budget tier from $200 to $2000 and beyond.
June 28, 2026Best GPUs for Coding Agents in 2026
Coding agents generate 10-50x more tokens per session than chatbots. Here is why bandwidth matters more than VRAM for agent workflows, and which GPUs deliver the best experience.
July 1, 2026Multi-GPU Setups for Local LLMs: The Complete Guide
Two RTX 3090s cost less than one RTX 6000 Ada and give you 48 GB of VRAM. Here is exactly how to set them up, what performance to expect, and the pitfalls to avoid.
July 1, 2026How to Choose Your First GPU for Local LLMs
Buying your first GPU for local LLMs? The single most important spec is VRAM: not cores, not clock speed, not brand. Here is exactly how to choose.
July 1, 2026Best GPUs Under $500 for LLMs (2026)
You do not need a $2000 GPU to run LLMs locally. For under $500, you can run 7-14B models comfortably. Here are the best options, including one with 16 GB of VRAM.
July 1, 2026Best GPUs $500-$1000 for LLMs (2026)
The $500-1000 range is where local LLMs get genuinely good. The used RTX 3090 with 24 GB dominates this tier: here is how every option compares.
July 1, 2026Best GPUs $1000+ for LLMs (2026)
Above $1000, you stop compromising. The RTX 5090's 32 GB and 1792 GB/s bandwidth make it the fastest consumer LLM GPU ever made. But is Apple Silicon the smarter buy?
July 1, 2026Used Enterprise GPUs for LLMs: A6000, A100, and Beyond
A used A6000 48GB costs less than a new RTX 4090 and runs models the 4090 cannot fit. Here is everything about the used enterprise GPU market for LLM inference.
July 1, 2026NVIDIA RTX 40 Series for LLMs: Complete VRAM & Performance Guide
From the 8 GB RTX 4060 to the 24 GB RTX 4090, here is exactly what each RTX 40 series card can run, at what speed, and which one offers the best value for LLM inference.
July 1, 2026NVIDIA RTX 50 Series (Blackwell) for LLMs: Complete Guide
The RTX 5090's 32 GB and 1792 GB/s make it the first consumer GPU that can technically run a 70B model. Here is the complete Blackwell lineup for LLM inference.
July 1, 2026Apple Silicon for LLMs: M1 to M6 Complete Guide (2026)
Apple Silicon's unified memory lets a single Mac run models no consumer GPU can touch. From the 8 GB M1 to the new 512 GB M5 Ultra, here's what each chip actually runs, and how fast.
August 25, 2026AMD Radeon for LLMs: ROCm & Vulkan Complete Guide
AMD GPUs offer more VRAM per dollar than NVIDIA, but the software setup is more involved. Here is everything you need to know about running LLMs on Radeon GPUs.
July 1, 2026Tutorials
How to Run LLMs Locally on Mac (M1–M4 Guide)
Apple Silicon's unified memory makes Macs surprisingly capable LLM machines. Here is what each M-series chip can actually run and how to set it up.
June 28, 2026GGUF Quantization Explained: Q4, Q5, Q6, Q8 Compared
Quantization is the single most important technique for running large models on consumer hardware. Here is how each GGUF quantization level actually works and when to use it.
June 28, 2026Getting Started with Ollama: Run Any LLM in One Command
Ollama makes running LLMs locally as simple as a single terminal command. Here is everything you need from installation to advanced customization.
June 28, 2026Getting Started with LM Studio: GUI-Based Local LLMs
LM Studio is the easiest way to run LLMs locally with a graphical interface. No terminal needed: here is how to set it up, pick your first model, and start chatting in under 5 minutes.
July 1, 2026llama.cpp Complete Setup Guide: Build, Configure, and Optimize
llama.cpp is the engine behind Ollama, LM Studio, and most local LLM tools. Learning it directly gives you maximum control over performance, VRAM usage, and context length.
July 1, 2026How to Benchmark Your Local LLM Setup
Is your GPU performing at full potential? Here is how to benchmark every aspect of your local LLM setup, from raw throughput to output quality, and compare against community results.
July 1, 2026Getting Started with Local LLMs (2026): The Complete Beginner's Guide
New to local LLMs? This guide takes you from zero to running your first model in under 10 minutes. No prior AI knowledge required, just a computer and internet.
July 1, 2026LLM Benchmarks Explained: MMLU, HumanEval, SWE-bench, and More
A model scoring 77 on SWE-bench sounds impressive, but what does it actually mean? Here is how to read benchmark scores and use them to pick the right model.
July 1, 2026Comparisons
GGUF vs EXL2 vs AWQ: Which Quantization Format to Use
Three quantization formats dominate local LLM inference. GGUF is universal, EXL2 is quality-optimal on NVIDIA, and AWQ is speed-focused. Here is how to choose.
June 28, 2026Ollama vs LM Studio vs llama.cpp: Which Tool Should You Use?
All three use the same inference engine under the hood, but the experience is radically different. Here is a detailed comparison to help you pick the right tool.
July 1, 2026Popular right now
How Much VRAM Does Llama 3 Need? Complete Guide
Find out exactly how much VRAM you need to run Llama 3 models locally, from the 8B variant on a budget GPU to the full 405B on multi-GPU setups.
July 30, 2026Best GPU for Running LLMs Locally in 2026
Buying a GPU for local LLMs? VRAM matters more than compute. Here is a practical buyer's guide covering every budget tier from $200 to $2000 and beyond.
June 28, 2026Getting Started with Local LLMs (2026): The Complete Beginner's Guide
New to local LLMs? This guide takes you from zero to running your first model in under 10 minutes. No prior AI knowledge required, just a computer and internet.
July 1, 2026GGUF vs EXL2 vs AWQ: Which Quantization Format to Use
Three quantization formats dominate local LLM inference. GGUF is universal, EXL2 is quality-optimal on NVIDIA, and AWQ is speed-focused. Here is how to choose.
June 28, 2026