Lesson 2100 of 2116
AI On-Device Models: Phi, Gemma, and the Edge Tradeoff
What current on-device AI models can do — and where edge inference falls short.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2on-device
- 3edge inference
- 4privacy
Concept cluster
Terms to connect while reading
Section 1
The premise
Small AI models like Phi and Gemma run on phones and laptops with strong privacy properties — but capability gaps versus cloud flagships remain large.
What AI does well here
- Privacy-preserving local inference
- Predictable latency without network
- Zero cost per inference after deployment
- Solid performance on narrow tasks like summarization
What AI cannot do
- Match flagship reasoning quality
- Handle long contexts without significant memory cost
Key terms in this lesson
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