Large Language Models (LLMs)
Different Large Language Models (LLMs) vary by developer (OpenAI's GPT, Google's Gemini, Meta's Llama, Anthropic's Claude), capabilities (multimodal, reasoning, coding), architecture (Transformer-based), and openness (proprietary vs. open-source), with current top models like GPT-4o, Gemini 2.5, Llama 3, Claude 3.5, and Mistral offering advanced text/image understanding for diverse tasks from chatbots to complex problem-solving.
Key LLM Families & Examples
- OpenAI: GPT-3, GPT-4, GPT-4o (highly capable, multimodal).
- Google: BERT, T5, Gemini (strong reasoning, multimodal).
- Meta: Llama (Llama 2, Llama 3), known for open-source approach.
- Anthropic: Claude (Claude 3, Claude 3.5 Sonnet), focuses on safety and nuanced dialogue.
- Mistral AI: Mistral models (Mixtral), popular open-weight models.
- xAI: Grok, integrated with X (Twitter) for real-time info.
- DeepSeek: DeepSeek-R1, V3, focusing on advanced reasoning.
Types & Architectures
- Generative (e.g., GPT): Predict next words for creative text, summaries.
- Encoder-Decoder (e.g., BERT): Bidirectional context for understanding, translation.
- Multimodal: Handle text, images (GPT-4V, Gemini).
- Instruction-Tuned/Dialog-Tuned: Trained for specific tasks or conversation (ChatGPT).
Key Differentiators
- Reasoning: Ability to solve complex, multi-step problems (DeepSeek R1, Gemini Pro).
- Multimodality: Processing text and images (GPT-4o, Gemini).
- Openness: Open-source (Llama, Mistral) vs. proprietary (GPT, Gemini).
- Application: General purpose (GPT-4o), coding (Copilot), or enterprise-focused (Cohere Command).