Choosing the right large language model can feel overwhelming with so many options out there, especially if you¡¯re not exactly living and breathing AI
But as we¡¯ve worked through each one, we¡¯ve gotten a real sense of what they¡¯re good at (and where they fall short).
So, let¡¯s talk about what to use, when.
ChatGPT & OpenAI-o1: The Reliable All-Rounders
Let¡¯s start with ChatGPT and OpenAI-o1.
OpenAI¡¯s latest model is impressive, and people are hyped about its ¡°reasoning¡± abilities ¡ª basically, it¡¯s designed to tackle more logic-heavy stuff alongside the creative tasks that ChatGPT has always been great at.
Why We Like It
- Big on Logic: OpenAI-o1 uses something called chain-of-thought reasoning. In simpler terms, it¡¯s better at walking through complex problems step by step.
- Custom GPTs: This feature lets us create models that remember instructions specific to our work. If we need it to think like a project manager or a social media assistant, we can set that up with just a few clicks.
Where It Falls Short
- Overkill for Basic Stuff: Most of the time, GPT-4 can get the job done. OpenAI-o1 shines with complex tasks, but you might not notice a huge difference for more straightforward use cases.
- Not a Quantum Leap: The big improvements are behind the scenes. If you¡¯re expecting to see massive changes in day-to-day use, you might be underwhelmed.
When to Use It: Anything involving more complex logic, or when you need tailored responses, like for coding or detailed content editing.
Claude by Anthropic: The Summarizer & Storytelling Champ
Claude is our go-to for summarizing and making sense of long documents.
It¡¯s also fantastic at storytelling, which is helpful if you¡¯re in content creation or need to simplify dense information.
What Makes It Stand Out
- Document Summarization: Claude is amazing at boiling down information, so it¡¯s perfect when we¡¯ve got huge documents m and need a quick summary.
- User-Friendly Customization: Anthropic¡¯s Projects feature lets us set up custom instructions for repeat tasks. It feels more intuitive than ChatGPT¡¯s setup.
What to Watch Out For
- File Size Limits: If you upload a big file (over 20 MB), Claude sometimes throws a fit. We usually compress PDFs to work around this, but it¡¯s worth knowing.
Best Use Case: Summarizing or creating content when you need a straightforward, reliable tool that¡¯s easy to navigate.
Google Gemini: The King of Context (and Podcasting)
Google¡¯s Gemini feels like it¡¯s in a league of its own when it comes to handling tons of data.
We love that it has a massive context window, meaning it can hold and process entire books if needed. Plus, it has a quirky new tool called Notebook LM that turns docs into a mini-podcast for you.
Why It¡¯s Cool
- Handles Huge Data Loads: With a 10-million-word limit, Gemini can keep track of massive documents all at once, so we can load entire libraries if we need to.
- Notebook LM: This feature actually turns documents into audio summaries in a conversational podcast format. It¡¯s a great way to get the gist of something while multitasking.
Drawbacks
- Limited Customization: While it has ¡°Gems¡± (Google¡¯s answer to custom GPTs), they¡¯re pretty basic. You can¡¯t connect it to other tools or APIs like you can with ChatGPT or Claude.
When to Turn to Gemini: When you need to process a mountain of data at once, or if you¡¯re in the mood for an audio summary while I¡¯m doing something else.
Llama by Meta: Privacy & Flexibility
Llama isn¡¯t necessarily the most advanced, but because it¡¯s open-source, it¡¯s our go-to when privacy is a concern.
Unlike the others, Llama can run offline on your computer, so it doesn¡¯t share data with a big tech company.
Why I¡¯d Recommend It
- Keeps Things Private: Since Llama runs locally, we can be sure our data stays off the internet.
- Highly Customizable: Llama¡¯s open-source, meaning we (or any developer) can modify it for unique needs. We don¡¯t do this much, but it¡¯s nice to know it¡¯s an option.
Weak Spots
- Not the Most Powerful: It¡¯s not as good as Claude or ChatGPT for high-quality content or problem-solving. But for basic use cases, it¡¯s solid.
When It Makes Sense to Use: Anytime privacy is key, like with sensitive internal data, or when you just need a quick local solution.
Grok by xAI: Twitter Data & Realistic Image Generation
Grok is a fun one ¡ª it¡¯s a social media native, integrated with X (formerly Twitter).
It¡¯s a decent model and comes with a strong image generator, Flux One, that can make super-realistic visuals. But where it really shines is pulling in Twitter data in real-time.
Why We Use It
- Live Twitter Insights: Grok lets us see what¡¯s trending or analyze popular Twitter profiles on the spot.
- Image Generation: Flux One can create realistic images of people, scenes, and more, with few limits on topics.
Downsides
- Niche Use Cases: It¡¯s great for Twitter data and images but doesn¡¯t stand out in general tasks like summarization or storytelling.
Ideal Use: Social media research and generating realistic visuals for content.
Perplexity: A Researcher¡¯s Best Friend
Perplexity isn¡¯t technically an LLM in the traditional sense. Instead, it¡¯s an AI-powered research tool that pulls information from the internet and then uses a model to organize it.
It¡¯s our go-to when I need quick, accurate information or a second opinion on a topic.
What Makes It Indispensable
- Web Search Capabilities: Perplexity searches the web and summarizes content, making it perfect for research-heavy tasks.
- Choose Your Model: we can use GPT-4, Claude, or even OpenAI-o1 as our ¡°engine¡± within Perplexity, so we always get the model that fits our needs.
Caveats
- Double-Check for Accuracy: Sometimes it mixes up similar names or pulls outdated info, so it¡¯s good to cross-check important facts.
When I Use Perplexity: Anytime I¡¯m in ¡°research mode¡± or need up-to-date insights for blog posts, presentations, or meetings.
Finding the right LLM can be as simple as matching a tool¡¯s strengths to your needs.
Our advice? Try out a few, and don¡¯t hesitate to mix and match to get the best results.