Not all LLMs are built the same.
Here’s the ultimate cheat sheet:
→ GPT = content & comms
→ Gemini = vision + audio
→ Mistral = speed & edge
→ DeepSeek = math + logic
How to master each (fast): 👇
1. BERT - The Reader
Made by Google (2018), BERT reads text in both directions.
It understands context deeply, making it great for:
→ Search engines
→ Sentiment analysis
→ Question answering
It’s the foundation of “understanding” in AI.
2. GPT - The Writer
Created by OpenAI, GPT predicts the next word in a sentence.
It’s decoder-only and excels at:
→ Generating fluent text
→ Storytelling
→ Prompt-based creativity
Think: ChatGPT, but trained at massive scale.
3. LLaMA - The Open Challenger
Meta’s open-source alternative to GPT.
Uses clever tricks (SwiGLU, RoPE) to rival models 10x its size.
→ Smaller, cheaper, surprisingly strong
→ Fueled massive community development
The underdog with real bite.
4. PaLM - The Few-Shot Master
Built by Google, PaLM is huge (540B) and optimized for:
→ Few-shot tasks
→ Reasoning
→ Multilingual performance
It powers Bard and Workspace AI. Smart, scalable, and serious.
5. Gemini - The Multimodal Beast
The evolution of PaLM.
Gemini understands text, images, code, and audio all in one model.
→ Massive context windows
→ Sparse expert layers
→ Enterprise-ready and phone-capable
This is Google's bet on the AI future.
6. Mistral - The Efficient Rebel
Small but mighty.
Mistral 7B beats much larger models using:
→ Grouped-query attention
→ Sliding windows
→ Sparse MoE in Mixtral
Open, fast, and crushing benchmarks with fewer parameters.
7. DeepSeek - The Reasoning Genius
From China’s High-Flyer AI.
Uses a Mixture-of-Experts (MoE) setup with 670B total params.
Only ~37B active per response = low cost, high IQ.
Excels at logic, math, multilingual tasks.
Like GPT-4’s smarter cousin.
LLMs aren’t one-size-fits-all.
Know what you’re building and choose the right model:
→ Reader? BERT
→ Writer? GPT
→ Open? LLaMA
→ Cheap + fast? Mistral
→ Multimodal? Gemini
→ Few-shot? PaLM
→ Reasoning? DeepSeek
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