Phi-3.5 Mini

Best on Edge

Microsoft

Released: 2024-08-20

Type: SLM (Small Language Model)

Context

128k

Max Out

4.1k

Cutoff

2024-06

Params

3.8B

The Breakdown

Phi-3.5 Mini challenges the assumption that you need a massive GPU to run AI. Microsoft trained this model on 'textbook quality' synthetic data, allowing it to punch way above its 3.8B parameter weight class. It can run smoothly on an iPhone or a standard laptop CPU while still offering a 128k context window. It represents the future of 'Local AI'—embedding intelligence directly into applications rather than relying entirely on cloud APIs.

Overall Score

8.5

/10

Pricing (per 1k tokens)

Input$0

Output$0

Currency: USD (Local)

The Good

Runs on a modern phone or laptop CPU
Massive 128k context in a tiny package
Surprisingly good at reasoning for its size

The Bad

Knowledge base is small (hallucinates facts easily)
Struggles with complex instruction following
Not a replacement for GPT-4 class models

The Verdict

The edge computing king. If you need to summarize a long document locally on a user's device without sending data to the cloud, Phi-3.5 is a miracle of engineering. Perfect for privacy-first apps.

Performance Benchmarks

drop

mmlu

human eval