AI Claude Tutorial: GPT, Gemini, Llama, The Lineup
TL;DRThe frontier-model landscape: Claude, GPT, Gemini, Llama — closed and open leaders.
A handful of labs lead: Anthropic's Claude, OpenAI's GPT, Google's Gemini (all closed, API-accessed), and Meta's Llama (open weights). They trade the lead on benchmarks frequently and differ in strengths (reasoning, coding, multimodality, context length, safety posture). Don't marry one — evaluate on your task, and design so you can swap providers as capabilities and prices shift.
Key points
Closed leaders: Claude, GPT, Gemini
Open leader: Llama (open weights)
Leadership and strengths shift often
Evaluate on your task; stay swappable
Common mistakes
Picking a model by hype/leaderboard alone
Hard-coupling to one provider’s API quirks
Ignoring price/latency/context differences
Try it: List factors to weigh when choosing a model for a real product.
Example code
<!doctype html><html><head><meta charset="utf-8"></head>
<body style="background:#06040d;color:#e6e0ff;font-family:monospace;padding:20px"><pre>weigh: task accuracy · cost · latency
context length · multimodality · safety
design to swap providers as things change</pre></body></html>