#model-families
5 articles
01
·Model Families·★ MEMBER·11 min read
Open vs Closed — The Economics of Releasing Weights, and the Safety Argument
Why would a company give away weights that cost a fortune to train? The decisive difference between open-weight and open-source, the licence clauses that actually cause incidents, and what each side of the release debate is really claiming — plus the convergence nobody expected. From no prior knowledge.
02
·Model Families·★ MEMBER·9 min read
The GPT Lineage — Design Thinking from GPT-1 to Today
A generation-by-generation walk from GPT-1 to GPT-4o and the reasoning models, asking what changed and what deliberately did not. At the centre sits one machine that only ever predicts the next token; what moved was scale, the order of training, and how the output was disciplined.
03
·Model Families·FREE·9 min read
The DeepSeek Family from Scratch — Breaking In with MoE and Distillation
DeepSeek redrew the open-LLM map with four tools: MoE, MLA, GRPO, and distillation. Walk the V2/V3/R1 lineage from zero prerequisites, learn how to read that famous training-cost number, and find out what the distilled models are actually for.
04
·Model Families·★ MEMBER·7 min read
The Qwen Family from Scratch — Why It Tops Hugging Face's Download Charts
Alibaba Cloud's Qwen is a fixture at the top of Hugging Face's download charts. From Qwen2.5's every-size-plus-specialist catalog strategy to Qwen3's thinking mode and MoE, this guide covers the lineage, why it excels at multilingual and code work, and the pitfalls that bite in production — assuming zero prior knowledge.
05
·Model Families·★ MEMBER·9 min read
The Llama Family from Scratch — The Main Line of Open LLMs
How Meta's Llama became the main line of open LLMs. The contrarian bet behind Llama 1, the lineage running through Llama 3.x, the llama.cpp / GGUF / Ollama ecosystem that grew around it, and the licensing traps to read before you ship commercially — starting from no prior knowledge.