ChatPlayground - Access the Best AI Models & Compare Them

Access the Best AI Models (25+) and Compare Them

Achieve Better AI Answers 73% more often with Multiple Chatbots I started ChatPlayground after finishing my research at UC Berkeley on which AI Model is the best. I compared 10 AI chatbots including ChatGPT-4o, Gemini 1.5 Pro, Llama 3.2, Perplexity, Bing Copilot and, much more. I found that each chatbots have their own perks, and that the only way to get the best response for your input is by using multiple chatbots at once 🤯. I used my own software to do this research but I had alot of demand to make it public, so ChatPlayground got started :)! This is what I learned about each chatbot: - ChatGPT-4o has really descriptive and usually longer answers, but prefers to answer in bullet points. - ChatGPT-4o was able to generate really nice data tables, that Gemini 1.5 Pro wasn't able to 📊. - Gemini 1.5 pro is great because it feels like it understands the context of your question more by having a conversational tone 💬. - Perplexity is good at giving you a completely answer, most AI Chatbots will give you bullet point answers, perplexity prefers to write out a complete answer rather than just giving bullet points 📝. - Bing Copilot is great because it cites its resources, will even recommend videos to help you 📹. - Bing copilot can be great but 20-30% of the time the answers it gives are not even usable 😐. - Because Bing copilot is using sources to give you answers the answers feel much more human like and at times more useful then other AI Chatbots that just list a bunch of basic bullet points 🤔. - Their should be no reason anyone is still using ChatGPT 3.5 or Gemini 1.0 today 🙅‍♂️. - Gemini 1.0 gives good answers but not as detailed and helpful as Gemini 1.5 Pro. - Llama is very very fast ⏱️ but doesn't always give you a detailed answer, mostly vague answers. - Mistral is great with longer prompts, but not so great with shorter prompts 📝. P.S. I asked all of the premium AI models on ChatPlayground to add emojis to this intro post, and I ended up choosing Llama 3.2 for the output.