Choosing the right large language model can feel overwhelming with so many options out there, especially if you\u2019re not exactly living and breathing AI<\/p>\n
But as we\u2019ve worked through each one, we\u2019ve gotten a real sense of what they\u2019re good at (and where they fall short).<\/p>\n
So, let\u2019s talk about what to use, when.<\/p>\n
<\/a><\/p>\n Let\u2019s start with ChatGPT and OpenAI-o1.<\/p>\n OpenAI\u2019s latest model is impressive, and people are hyped about its \u201creasoning\u201d abilities \u2014 basically, it\u2019s designed to tackle more logic-heavy stuff alongside the creative tasks that ChatGPT has always been great at.<\/p>\n Big on Logic<\/strong>: OpenAI-o1 uses something called chain-of-thought reasoning. In simpler terms, it\u2019s better at walking through complex problems step by step. <\/p>\n Custom GPTs<\/strong>: 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. <\/p>\n Overkill for Basic Stuff<\/strong>: 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. <\/p>\n Not a Quantum Leap<\/strong>: The big improvements are behind the scenes. If you\u2019re expecting to see massive changes in day-to-day use, you might be underwhelmed. <\/p>\n When to Use It<\/strong>: Anything involving more complex logic, or when you need tailored responses, like for coding or detailed content editing.<\/p>\n Claude is our go-to for summarizing and making sense of long documents.<\/p>\n It\u2019s also fantastic at storytelling, which is helpful if you\u2019re in content creation or need to simplify dense information.<\/p>\n Document Summarization<\/strong>: Claude is amazing at boiling down information, so it\u2019s perfect when we\u2019ve got huge documents m and need a quick summary. <\/p>\n User-Friendly Customization<\/strong>: Anthropic\u2019s Projects feature lets us set up custom instructions for repeat tasks. It feels more intuitive than ChatGPT\u2019s setup. <\/p>\n File Size Limits<\/strong>: If you upload a big file (over 20 MB), Claude sometimes throws a fit. We usually compress PDFs to work around this, but it\u2019s worth knowing. <\/p>\n Best Use Case<\/strong>: Summarizing or creating content when you need a straightforward, reliable tool that\u2019s easy to navigate.<\/p>\n Google\u2019s Gemini feels like it\u2019s in a league of its own when it comes to handling tons of data.<\/p>\n 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.<\/p>\n Handles Huge Data Loads<\/strong>: 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. <\/p>\n Notebook LM<\/strong><\/a>: This feature actually turns documents into audio summaries in a conversational podcast format. It\u2019s a great way to get the gist of something while multitasking. <\/p>\n Limited Customization<\/strong>: While it has \u201cGems\u201d (Google\u2019s answer to custom GPTs), they\u2019re pretty basic. You can\u2019t connect it to other tools or APIs like you can with ChatGPT or Claude. <\/p>\n When to Turn to Gemini<\/strong>: When you need to process a mountain of data at once, or if you\u2019re in the mood for an audio summary while I\u2019m doing something else.<\/p>\n Llama isn\u2019t necessarily the most advanced, but because it\u2019s open-source, it\u2019s our go-to when privacy is a concern.<\/p>\n Unlike the others, Llama can run offline on your computer, so it doesn\u2019t share data with a big tech company.<\/p>\n Keeps Things Private<\/strong>: Since Llama runs locally, we can be sure our data stays off the internet. <\/p>\n Highly Customizable<\/strong>: Llama\u2019s open-source, meaning we (or any developer) can modify it for unique needs. We don\u2019t do this much, but it\u2019s nice to know it\u2019s an option. <\/p>\n Not the Most Powerful<\/strong>: It\u2019s not as good as Claude or ChatGPT for high-quality content or problem-solving. But for basic use cases, it\u2019s solid. <\/p>\n When It Makes Sense to Use<\/strong>: Anytime privacy is key, like with sensitive internal data, or when you just need a quick local solution.<\/p>\n Grok is a fun one \u2014 it\u2019s a social media native, integrated with X (formerly Twitter).<\/p>\n It\u2019s 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.<\/p>\n Live Twitter Insights<\/strong>: Grok lets us see what\u2019s trending or analyze popular Twitter profiles on the spot. <\/p>\n Image Generation<\/strong>: Flux One can create realistic images of people, scenes, and more, with few limits on topics. <\/p>\n Niche Use Cases<\/strong>: It\u2019s great for Twitter data and images but doesn\u2019t stand out in general tasks like summarization or storytelling. <\/p>\n Ideal Use<\/strong>: Social media research and generating realistic visuals for content.<\/p>\nChatGPT & OpenAI-o1: The Reliable All-Rounders<\/strong><\/h2>\n
Why We Like It<\/strong><\/h3>\n
Where It Falls Short<\/strong><\/h3>\n
Claude by Anthropic: The Summarizer & Storytelling Champ<\/strong><\/h2>\n
What Makes It Stand Out<\/strong><\/h3>\n
What to Watch Out For<\/strong><\/h3>\n
Google Gemini: The King of Context (and Podcasting)<\/strong><\/h2>\n
Why It\u2019s Cool<\/strong><\/h3>\n
Drawbacks<\/strong><\/h3>\n
Llama by Meta: Privacy & Flexibility<\/strong><\/h2>\n
Why I\u2019d Recommend It<\/strong><\/h3>\n
Weak Spots<\/strong><\/h3>\n
Grok by xAI: Twitter Data & Realistic Image Generation<\/strong><\/h2>\n
Why We Use It<\/strong><\/h3>\n
Downsides<\/strong><\/h3>\n
Perplexity: A Researcher\u2019s Best Friend<\/strong><\/h2>\n