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Best Free Web Resources — local AI tools and hardware guides

Best Free Web Resources

Local AI Tools & Digital Engineering Resources

What can I run?
  • AI Tools
    • Start: Local LLMs
    • Ollama Models & VRAM
    • LM Studio Models
    • GPU Comparison
    • AI Hardware Matrix
    • Local LLM Directory
    • VRAM Calculator
    • Hardware Compare
    • Local Model Recommender
    • API Pricing & ROI
  • Local AI Guides
  • Web Resources
    • Inspiration
    • Photography
    • Games
    • SEO
    • Tutorial
      • Coding
      • WordPress
    • Resume/CV
    • Graphics
      • Logo
    • Freebies

What do you want to do?

Free calculators and hardware data for running AI models on your own machine — every figure computed from published specifications, never benchmarked in-house.

See what my PC can run Pick your VRAM, get the models that fit and the quantization each one needs. Pick a GPU for AI What each VRAM tier actually unlocks, and why capacity beats raw speed. Fine-tune a model LoRA, QLoRA or full fine-tuning — the memory each one really costs. Train an image LoRA Flux, SDXL and SD 3.5, including the caching step that saves gigabytes. Compare my options GGUF vs AWQ, Ollama vs vLLM, fine-tuning vs RAG — and hardware head-to-heads.

The calculators

Answer a sizing question in seconds instead of reading a forum thread.

VRAM Calculator Model weights, KV cache and framework overhead for any model and context length. Inference GGUF Size Calculator File size at every quantization level, from bits per weight measured on real GGUF files. Quantization Fine-tuning VRAM Weights, gradients, optimizer state and activations for LoRA, QLoRA and full fine-tuning. Training LoRA Training VRAM Image-model LoRAs for Flux, SDXL, SD 3.5 and Qwen-Image at any rank and resolution. Training Image Generation VRAM Peak memory by precision and offload strategy, computed per component. Diffusion Mac VRAM Optimizer How much unified memory your Apple Silicon GPU can actually address. Apple Silicon

Start from the memory you have

Every model in our directory, scored against what a card that size realistically gives you.

8GBEntry 12GB14B models 16GBRecommended 24GB32B models 32GBLong context 48GB70B models 64GBWorkstation 128GBUnified memory

Latest guides

Hardware sizing, quantization and local-model setup, with sources on every claim.

Mac mini M6 for local AI: memory bandwidth of the M6 16GB, M6 24-32GB and M5 Pro configurations

Mac mini M6 for Local AI: Which Configuration to Buy, and Why 16GB Is Slower

Rupesh Kumar
October 14, 2026

The 2026 Mac mini comes with an M6 or an M5 Pro chip, and Apple pitches both at local AI. Its product page says…

Continue Reading Mac mini M6 for Local AI: Which Configuration to Buy, and Why 16GB Is Slower

Window listing the three places an LM Studio Bionic session can run a model: Local, Remote via LM Link, and Secure Cloud

LM Studio Bionic: What It Does, What It Costs, and What Stays Local

BFWR Editorial
October 14, 2026

LM Studio Bionic is LM Studio’s AI agent: an app that can work through a codebase, edit documents and research a topic, using open…

Continue Reading LM Studio Bionic: What It Does, What It Costs, and What Stays Local

Terminal window showing the llmfit, llmfit recommend, llmfit bench and llmfit doctor commands

llmfit: How the Local LLM Fit Checker Works, and How Far to Trust It

Rupesh Kumar
October 13, 2026

llmfit answers the first question everyone asks about local AI: which models will actually run on this machine? It is a free, MIT-licensed command-line…

Continue Reading llmfit: How the Local LLM Fit Checker Works, and How Far to Trust It

Directories and data

The reference tables behind the calculators.

Models Directory Parameter counts, licences and memory requirements for open-weight models. 30 models Hardware Matrix Laptops, desktops and GPUs profiled against the models each one can run. 75 devices Licence Checker What each model licence actually permits, including commercial use and derivatives. Before you ship API Pricing & ROI Current per-token rates, so you can work out your own break-even against hardware. Local vs cloud

Pick a runner

The software that actually loads the model, and what each one costs in memory.

Ollama Every model’s memory cost and the pull command that fetches it. Easiest start LM Studio Memory cost, lms commands, and MLX builds on Apple Silicon. Desktop app llama.cpp The engine underneath most runners, with the flags that control memory. Full control vLLM Serving throughput, and why it reserves the whole card up front. Replacing an API Open WebUI The chat interface to put in front of a runner, and what to pair it with. Front end ComfyUI Peak VRAM for every diffusion model, by precision and offload mode. Image generation Self-Hosted AI What running it yourself protects, and the three layers of the stack. Start here for why

Free web resources

The wider BFWR archive — design assets, development tutorials and free tools.

Technology Coding Tutorials Freebies Graphics WordPress SEO

How to Run GLM-5.3-Flash Locally: 321B, MIT Licence, and the Memory It Takes

Continue Reading How to Run GLM-5.3-Flash Locally: 321B, MIT Licence, and the Memory It Takes

Why Modern Online Slots Feel Different Even When the Basic Format Looks the Same

Continue Reading Why Modern Online Slots Feel Different Even When the Basic Format Looks the Same

How to Run Qwen3.8-Flash-Next Locally: Memory, Speed and the Licence Catch

Continue Reading How to Run Qwen3.8-Flash-Next Locally: Memory, Speed and the Licence Catch

DGX Spark vs Strix Halo for Local AI: Same Memory Bus, Very Different Price

Continue Reading DGX Spark vs Strix Halo for Local AI: Same Memory Bus, Very Different Price

Two 16GB Graphics Cards Can Be 3.3x Apart for Local AI

Continue Reading Two 16GB Graphics Cards Can Be 3.3x Apart for Local AI

AI Upscale Models in 2026: Which Still Ship, and Which You Cannot Sell

Continue Reading AI Upscale Models in 2026: Which Still Ship, and Which You Cannot Sell

ControlNet Models in 2026: Which Ones Still Ship, and What They Weigh

Continue Reading ControlNet Models in 2026: Which Ones Still Ship, and What They Weigh

Stable Diffusion LoRA: Matching the Base Model, Weights and Stacking

Continue Reading Stable Diffusion LoRA: Matching the Base Model, Weights and Stacking

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Latest Guides

  • Mac mini M6 for Local AI: Which Configuration to Buy, and Why 16GB Is Slower
  • LM Studio Bionic: What It Does, What It Costs, and What Stays Local
  • llmfit: How the Local LLM Fit Checker Works, and How Far to Trust It
  • How to Run GLM-5.3-Flash Locally: 321B, MIT Licence, and the Memory It Takes
  • Why Modern Online Slots Feel Different Even When the Basic Format Looks the Same
  • How to Run Qwen3.8-Flash-Next Locally: Memory, Speed and the Licence Catch

AI Tools & Calculators

  • What can I run?
  • VRAM Calculator
  • GGUF Size Calculator
  • Fine-tuning VRAM
  • LoRA Training VRAM
  • Image Generation VRAM
  • Mac VRAM Optimizer

Browse & Compare

  • Models Directory (30 models)
  • Hardware Matrix (75 devices)
  • Image Models
  • Model Licences
  • Comparisons
  • Model Recommender
  • API Pricing & ROI

Guides & Resources

  • Technology
  • Coding
  • Tutorials
  • Freebies
  • Graphics

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