Lesson 1253 of 1570
Why Haiku, GPT-4o-mini, and Gemini Flash Often Win in Production
Small models are fast enough for users to feel snappy and cheap enough to deploy at scale.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The big idea
- 2small models
- 3Haiku
- 4GPT-4o-mini
Concept cluster
Terms to connect while reading
Section 1
The big idea
Frontier models grab the headlines but small fast models like Claude Haiku, GPT-4o-mini, and Gemini Flash do most of the actual production work. They're fast enough to feel real-time and cheap enough to run on every request.
Some examples
- A search-suggestion feature runs on Haiku at <300ms per request — frontier latency wouldn't work.
- GPT-4o-mini handles 90% of customer support tickets at 1/30th the cost of GPT-4o.
- Gemini Flash classifies emails into folders fast enough to feel instant.
- A grammar checker on every keystroke needs Haiku-class latency, not Opus-class smarts.
Try it!
Profile a feature you're building. If response time matters, swap to Haiku or GPT-4o-mini. Measure the difference.
Key terms in this lesson
End-of-lesson quiz
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