🤯 Too Many GPTs, Not Enough Clarity: When to Use What (and Why)
🧠 Binary Banter Decodes the LLM Jungle So You Don’t Have To
👩💻 Rin: “Obito! There are too many GPTs. Every week, a new one drops like it’s the next iPhone. I just wanted help writing an email—not choose from 12 language models!”
👨💻 Obito: “It’s LLM bingo now. But don’t worry—I’ll help you pick the right model for the job. Think of it like choosing the right Pokémon. You wouldn’t bring a Pikachu to a lava fight.”
👩💻 Rin: “I don’t want to bring GPT-4 to a summarization job if Claude is already sipping the abstract like it’s tea.”
📦 Why So Many GPTs?
🧬 Open-source boom (LLaMA, Mistral, Gemma)
🤝 Company ecosystems (OpenAI, Google, Anthropic, xAI)
⚙️ Model specialization (reasoning, creativity, coding, real-time)
🌐 API availability vs local deployment
👨💻 Obito: “Each model’s trained differently, excels at different tasks, and has its own quirks. Let’s break it down.”
🧭 Model Map: When to Use What (2025 Edition)
💼 Category 1: General-Purpose All-Stars
👨💻 Category 2: Coders & Debuggers
🎨 Category 3: Creativity & Writing
🧠 Category 4: Multimodal & Agents
🧩 Other Things to Consider
Latency → GPT-4o is fastest, Claude 3 Opus is slower but detailed
Context size → Claude rules the memory game (200K)
Privacy → Open-source wins in air-gapped and private builds
Pricing → Claude & Gemini are cheaper/free for most casual use
🧠Quick Pick Guide
🎤 Final Banter
👩💻 Rin: “So LLMs are like ramen flavors—pick based on the mood, the spice, and the deadline?”
👨💻 Obito: “Exactly. Just don’t bring Gemini to a coding fight or Mistral to a philosophy debate.”
👩💻 Rin: “Got it. And if I still can’t decide?”
👨💻 Obito: “Use GPT-4o. It’ll explain your options with citations and a haiku.”
🚀 Follow BinaryBanter on Substack, Medium | 💻 Learn. Discuss. Banter.