Navigate the crowded AI model market with confidence. Understand the real tradeoffs between Claude, GPT, Gemini, and open-source models — and make smarter choices for your use case.
Claude Fable 5 and Mythos 5: SOTA Autonomy and Safeguards
What Anthropic shipped and what it means for agentic work.
GPT-5.6: Sol, Terra, and Luna Models Explained
OpenAI's tiered model lineup, pricing, and benchmarks.
Google Gemini 3.5: Complete Guide
Gemini 3.5 Flash, Omni, Deep Think — Google's full model family explained.
Meta Llama 4: Open-Source AI Complete Guide
Scout, Maverick, Behemoth — running open-weight models locally and in production.
GPT-5.6 vs Claude Fable 5: Benchmark Comparison
Side-by-side on coding, reasoning, and agentic tasks.
DeepSeek V4 Pro: Agent Coding Benchmarks and API Economics
The Chinese model that disrupts pricing assumptions.
What Is Fine-Tuning an LLM?
When and how to specialize a model for your domain.
What Is AI Model Quantization?
Running frontier AI locally — the technical tradeoffs explained.
Run 70B LLMs on a 4GB GPU with AirLLM
No quantization, no expensive hardware — how it works.
Closed-Source AI vs Local Open-Source Alternatives
Privacy, cost, and capability tradeoffs for 2026.
Model selection depends on your task type, cost constraints, context requirements, and whether you need multimodal capabilities. This pathway gives you the frameworks to compare: benchmark performance on tasks similar to yours, pricing at your expected volume, context window requirements, and whether you need API access or a consumer product. It also covers open-source alternatives for privacy-sensitive or cost-sensitive applications.
The specific model comparisons (GPT-5.6 vs Claude Fable 5) reflect the 2026 landscape and will evolve. The evaluation frameworks — how to read benchmarks, how to think about fine-tuning vs prompting, how to assess quantization tradeoffs — are durable skills that apply regardless of which specific model versions are current.
10 articles, approximately 6 hours. This is an intermediate pathway that pairs well with AI Foundations for a complete picture of both the architecture and the market landscape.
Understand what AI actually is — tokens, transformers, agents, and the landscape. Start here if you're new.
10 articles · ~4h →Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.
11 articles · ~5h →Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.
13 articles · ~7h →Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous.
11 articles · ~6h →Practical AI adoption for your specific function — marketing, engineering, HR, finance, and more.
10 articles · ~4h →The technical foundations every AI builder needs — APIs, Git, Docker, Python, Next.js, and modern web.
10 articles · ~6h →
