AI Response Latency: How to Keep Users Engaged When GPT Takes 10 Seconds
GPT-4 takes 196ms per token. Reasoning models need 45-120 seconds. Here's how to keep users engaged instead of watching them close the tab during your AI's thinking time.
October 13, 2025 6 min read
Your AI feature works perfectly. The responses are accurate, helpful, and exactly what users need. There's just one problem: they close the tab before seeing them.
GPT-4 generates text at roughly 196ms per token. A 500-token response takes nearly 100 seconds without streaming. Reasoning models like o1 need 45-120 seconds just to start responding. Your users don't have that kind of patience. This is one of the biggest challenges we solve in AI development projects.
The latency problem isn't going away. Models are getting smarter, not faster. You need UX patterns that keep users engaged during the wait.
The Streaming Implementation That Changes Everything
Streaming transforms the perception of latency. Instead of waiting 100 seconds for a complete response, users see the first token in 2-3 seconds.
The psychological difference is massive:
Complete response: 100-second blank screen, then wall of text
Streamed response: 3-second wait, then continuous engagement
User perception: "broken" vs "working"
Implement streaming with OpenAI's SDK:
The first token arriving in 2-3 seconds tells users the system is working. Each subsequent token maintains engagement. The total time hasn't changed, but the experience is completely different.
What most teams get wrong: They implement streaming but batch tokens into chunks of 10-20 before sending to the frontend. This defeats the purpose. Send individual tokens or very small chunks (2-3 tokens max).
Loading States That Actually Communicate Progress
Spinner animations are lazy UX. They tell users "something is happening" but nothing about what or how long.
Most marketing automation apps treat AI as a feature to add later. Here's why that approach fails—and how to architect AI-native marketing automation from day one.
// Send immediate acknowledgmentsocket.emit("status", "Processing...");// Start fast model for initial responseconst quickResponse = await openai.chat.completions.create({ model: "gpt-4.1-mini", messages: [{ role: "user", content: "Acknowledge this query: " + userQuery }], stream: true,});// Simultaneously start slow model for complete responseconst fullResponse = await openai.chat.completions.create({ model: "gpt-4", messages: fullMessages, stream: true,});
javascript
// Don't disable input during AI responseinput.disabled = false;// Queue new messages instead of blockingif (aiIsResponding) { queueMessage(newMessage); showNotification("Message queued, will send after current response");}
javascript
const TIMEOUT_THRESHOLD = 30000; // 30 secondsconst timeout = setTimeout(() => { showFallbackOptions({ email: "Email me when ready", simplify: "Get faster, simpler response", cancel: "Cancel and try different query", });}, TIMEOUT_THRESHOLD);// Clear timeout when response completesresponse.on("complete", () => clearTimeout(timeout));
