What's the difference between using Claygent Neon and GPT 4o mini?

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What's the difference between using Claygent Neon and GPT 4o mini AI enrichment to run a prompt?

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Claygent Neon and GPT-4 have distinct characteristics: Claygent Neon: ** Is our flagship model specifically designed for agent tasks ** Excels in answer formatting and data extraction ** Can format results into multiple columns or outputs ** Has shown the highest accuracy in internal testing ** Performs better at parsing PDFs and finding hard-to-find information ** Costs 2 credits per useGPT-4: ** Offers enhanced reasoning capabilities ** Better suited for complex analytical tasks ** Doesn't provide the same level of answer formatting as Neon ** Can be useful for testing data accuracy * Costs 3 credits per row when using Clay keyNote: There isn't a "GPT-4o mini" model mentioned in our documentation. You might want to double-check the specific model name you're referring to. Sources: Claygent: AI Web Scraper [CRM Enrichment] - Clay University Introducing Claygent Neon
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Claygent Neon and GPT-4 have distinct characteristics: Claygent Neon: ** Is our flagship model specifically designed for agent tasks ** Excels in answer formatting and data extraction ** Can format results into multiple columns or outputs ** Has shown the highest accuracy in internal testing ** Performs better at parsing PDFs and finding hard-to-find information ** Costs 2 credits per useGPT-4: ** Offers enhanced reasoning capabilities ** Better suited for complex analytical tasks ** Doesn't provide the same level of answer formatting as Neon ** Can be useful for testing data accuracy * Costs 3 credits per row when using Clay keyNote: There isn't a "GPT-4o mini" model mentioned in our documentation. You might want to double-check the specific model name you're referring to. Sources: Claygent: AI Web Scraper [CRM Enrichment] - Clay University Introducing Claygent Neon
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Was that helpful?
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Hi Joe Hannon! This thread was recently closed by our Support team. If you have a moment, please share your feedback: