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When to Use Perplexity, Claygent, and ChatGPT AI Models
any insights on when to use each AI model? Perplexity vs Claygent vs ChatGPT
We offer different AI models within Clay, each with specific strengths: 1. Perplexity AI: Best for web searches and information retrieval. Use it when you need to find up-to-date information online. 2. Claygent models: • Helium: Excellent price-performance ratio, outperforming Haiku and GPT 4o-Mini. • Neon: Excels in answer formatting and data extraction. Good for complex tasks at a reasonable price. • Argon: Strongest for deep research and complex analysis. 3. GPT-4 and Claude Opus: Offer enhanced reasoning capabilities. Use these for testing data accuracy or handling complex analytical tasks that require advanced reasoning. Choose the model based on your specific needs, considering factors like task complexity, data extraction requirements, and reasoning capabilities.
Bruno R.··Hi Theo, thanks for your message—happy to help! Let’s start by clarifying the distinction between Perplexity and Claygent. Claygent is our in-house web research tool, designed for high performance when querying unstructured data and retrieving structured results. While Perplexity provides similar web research capabilities, Claygent goes a step further by letting you structure and format the output—making it easier to push into your system of record. As for ChatGPT, our foundational model integrations specialize in reasoning over existing data to generate content—such as text, summaries, or snippets—but they’re not optimized for live data retrieval or web research.
Theo K.··I am creating a post for Clay, would this make sense? I am asking to ensure I provide accurate information. I will tag you in the post for credits 🙂 🔍 Looking for Data Analysis? → Claude (Anthropic) Perfect for combining multiple data points and spotting patterns across rows. ✍️ Want emails that don’t sound like AI? → Saunet It writes like a human. Seriously. Super effective for outbound copy, but also to create your next break-up text. 🌐 Need up-to-date info from the web? → Perplexity AI Ideal for pulling recent company news, roles, funding rounds, etc. ⚙️ Claygent Models (Many people overlook their power as they let you structure your output): 🚀 Helium – Best price-to-performance ratio. Great for general tasks. 🟡 Neon – Excels at answer formatting + data extraction. 🔬 Argon – Strongest for deep research and reasoning-heavy tasks. My favorite when it comes to analyzing websites and qualifying prospects. 🧠 Trying to get advanced reasoning? → GPT-4 (Open AI) or Claude Opus Use these for high-stakes analysis, cross-checking data accuracy, or multi-step logic. ⚡️Using the right model = faster workflows, better results, lower costs. Save this for your next Clay build. And if you’re unsure what to pick, ask Nikos, Alkaios or Elena. They’ve tested them all.
- Bruno R.··
Looks great! Just a quick note on this section: "→ GPT-4 (Open AI) or Claude Opus Use these for high-stakes analysis, cross-checking data accuracy, or multi-step logic." GPT-4 is not a reasoning model - OpenAI's orion series is instead. This includes o1, o3, etc.
- Theo K.··
thanks mate