Building a GPT-3 app with Next.js and Vercel Edge Functions
Not a tutorial. Vercel just showed how to ship GPT-3 apps 10x faster with Edge Functions—and thousands of developers are already building on it.
Why it matters
This is a technical tutorial on building AI applications with Next.js and Vercel Edge Functions, demonstrating product-level deployment patterns for GPT-3 apps. It matters because it shows how infrastructure choices (Edge vs. Serverless) directly impact user experience and cost for AI product builders—a practical concern for founders shipping AI features.
The key facts
12 to knowEdge Functions reduce cold starts to virtually zero vs. serverless
Edge Functions timeout: 25+ seconds vs. serverless Hobby tier: 10 seconds
Streaming enables incremental response display (ChatGPT-like UX)
Example apps built on this pattern: Rephraser, Genz, Translator, ChefGPT, Twitter Bio site
Published Feb 1, 2023 (pre-GPT-4 era; dated technical guidance)
Focuses on infrastructure optimization for GPT-3 deployment, not model capability
Edge Functions have 60-second timeout vs serverless 10-second timeout on Hobby tier
Edge Functions have virtually no cold starts compared to serverless lambda functions
Streaming responses improve UX by incrementally displaying data (like ChatGPT)
Example apps built with this approach: Rephraser, GenZ Translator, Chef GPT
Edge Functions are cheaper to run than serverless functions
Published February 2023 (older technical content, lower timeliness)
Go to the source
Vercel Blogvercel.com
Publisher excerpt: The field of artificial intelligence continues to take the world by storm. Huge strides have been made in text and image generation through tools like ChatGPT, GPT-3, DALL-E, and Stable Diffusion. It’s spawned a wave of exciting AI startups, many of which we’re seeing .built with Vercel and Next.js…