LET'S DEFINE THE PIECES

Everything you need to know falls into one of three categories:

1. MODELS (LLMs)

  • These are the brains.
  • They are NOT software.
  • They are NOT programs.
  • They are NOT plugins.
  • They are neural networks stored in a single file, usually:

model.gguf
model.safetensors
model.bin


Examples of models:
LLaMA-3 8B
LLaMA-3 70B
Mistral 7B
Mixtral 8x7B
Qwen 2 7B
Phi-3

A model file contains:
Neurons
Synapses
Every learned pattern
All the intelligence

A model does NOT:

  • Have a UI
  • Open PDFs
  • Connect to NASA
  • Run indexing
  • Provide a chat window


It only takes text in → text out.

2. MODEL RUNTIMES (ENGINES)

These are the programs that LOAD and RUN the model's brain.
Think of a “runtime” as the machine that runs a model file.

===== Runtimes include ===== :
✔ Ollama

  • Terminal-based
  • Local API
  • Can fine-tune
  • Good for automation
  • Good for pipelines
  • Very flexible
  • Acts like a backend server

✔ LM Studio

  • GUI desktop app
  • Easy model downloading
  • Drag-and-drop PDFs
  • File chat
  • Rudimentary RAG
  • Easy to test many models
  • Great for tinkering

✔ GPT4All

  • GUI
  • Also a runtime
  • Similar to LM Studio
  • Not as modern

✔ koboldcpp

  • Runtime specialized for story-writing/roleplay
  • GUI
  • Some fine-tuning tools

✔ Faraday / Unsloth / Axolotl (training tools, not chatbots)

These are training engines, not chat apps.

You don’t talk to them; you use them to train a model.

Summary

Models = The brains
Runtimes = The engines that run the brains
Training tools = The machines that modify the brains

3. TRAINING TOOLS (NEURAL LEARNING, “NEW SYNAPSES”)

This is where real learning happens. Not prompts. Not memory.
Not RAG. (library model), Actual neural adjustment. 

\code\

Tools include: ✔ Axolotl

  • THE standard for fine-tuning LLaMA, Mistral, etc.
  • Used by researchers, labs, and giants.

✔ Unsloth

  • A faster, more GPU-efficient training toolkit.
  • Great for consumer GPUs like yours.

✔ Faraday

  • A more experimental training tool, but advanced.


* These tools: * Read your dataset

  • Modify the model’s weights
  • Produce a new personalized model

This is real learning.