Llm Platforms
Meta's Llama is the model family that made local AI real. It is not the most capable model available — Claude, GPT, and Gemini all beat it on hard tasks. But it is the model you can run on your own hardware, fine-tune on your own data, and deploy
Llm Platforms
OpenAI's model lineup in 2026 is a capable but confusing product. GPT-4o is the multimodal daily driver that handles most tasks well. GPT-4.5 is the reasoning tier that costs more and thinks harder. The challenge is that "ChatGPT" refers to at least four different experiences
Llm Platforms
This is the last article in the series, and I'm going to do the thing that most comparison articles refuse to do: give you a direct answer. Not "it depends." Not a matrix with seventeen dimensions and no conclusion. An actual recommendation based on who you
Llm Platforms
Google's Gemini is the LLM platform that keeps almost delivering. It has the largest context window in production, the best integration with productivity tools you already use, and a pricing model that undercuts everyone. It is also the platform where the gap between demo and daily reality is
Llm Platforms
The pricing pages for LLM platforms are designed to make you think $20/month gets you unlimited access to the most powerful AI models available. It doesn't. What $20 gets you is a taste — enough to build a habit, not enough to sustain a workflow. And the real
Llm Platforms
If you use AI to understand things — analyze documents, compare sources, extract patterns from data, make sense of a pile of PDFs you don't have time to read — the model you choose matters more than for almost any other task. Writing quality is subjective. Code either runs or
Llm Platforms
Every model can write. That's the baseline now — you type a prompt, you get grammatically correct paragraphs back. The question that actually matters in 2026 is which model writes the thing you need, in the way you need it, without requiring forty-five minutes of prompt engineering to get
Llm Platforms
Picking the right LLM for coding is not a single decision. It's five or six decisions, because "coding" covers tasks that have almost nothing in common with each other. Autocomplete while you type, generating a new module from a description, refactoring a legacy codebase, debugging a
Llm Platforms
The open-vs-closed debate in LLMs generates more heat than light, mostly because people argue ideology when they should be doing math. Running your own model is not inherently better or worse than calling an API. It depends on what you're doing, how much you're doing it,
Llm Platforms
Most serious LLM users should have access to both Claude and GPT. That's the conclusion, up front, because every head-to-head comparison that declares a single winner is optimizing for clicks over usefulness. These models have genuinely different strengths, and those differences are stable enough now that you can
Llm Platforms
Anthropic's Claude is the LLM platform that serious text workers migrated to and mostly stayed on. It is the best model family available for long-form writing, complex instruction following, and code editing. It is not the best at everything, and it costs more than you expect once you
Leapfrog
There's a version of you that signed up for every AI tool the week it launched. That version has 14 accounts, 9 browser extensions, a Notion database of "tools to try this weekend," and the vague feeling of being behind despite spending more time evaluating tools