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ModelsPhi-4 14B

Phi14B

Phi-4 14B

Microsoft's research model optimized for STEM and reasoning — punches well above its 14B weight on math and logic.

14B

parameters

16GB

minimum RAM

Overview

What makes Phi-4 14B notable

Phi-4 14B is a Microsoft Research model trained with an emphasis on synthetic, high-quality reasoning data. Rather than being trained on massive raw text, Phi-4 was trained on curated educational content, textbooks, and structured problem sets — giving it disproportionate capability on STEM tasks relative to its size.

On math benchmarks and structured reasoning tasks, Phi-4 14B outperforms many larger general-purpose models. It's particularly strong on problems that require step-by-step logical thinking — which makes it a favorite for STEM professionals and anyone who needs reliable analytical output.

The 16GB RAM requirement makes it accessible on a 24GB Mac Mini, where it runs at high quantization and delivers fast, reliable output. Think of it as a reasoning specialist: not the model for casual chat, but the one you reach for when accuracy and methodology matter.

Best use cases

What it excels at

  • Mathematical problem-solving from high school to graduate level
  • STEM Q&A and technical concept explanation
  • Structured logic and formal reasoning tasks
  • Physics, chemistry, and engineering calculations
  • Statistical analysis and data interpretation
  • Study assistance and academic problem-solving

Compatibility

Hardware requirements

Mac modelRAMPerformanceNotes
Mac Mini M4 Pro24GBGreatQ6/Q8 quantization — high quality output
Mac Mini M4 Pro48GBExcellentQ8 quantization — maximum quality
Mac Studio M4 Max128GBOptimalQ8 quantization — blazing fast, full quality
Mac Studio M3 Ultra192GB+OptimalQ8 full precision — run multiple models simultaneously

Speed

Approximate tokens/second

Mac Mini M4 Pro 24GB~30 tok/s
Mac Mini M4 Pro 48GB~45 tok/s
Mac Studio M4 Max 128GB~110 tok/s
Mac Studio M3 Ultra 192GB+~180 tok/s

Use case fit

Quality ratings

Chat
Coding
Reasoning
Creative Writing
Document Analysis

Cost comparison

Without local AI, the equivalent capability costs:

Cloud equivalent

GPT-3.5 Turbo (but much better at reasoning)

~$80/moper month

Local with Maai Machines

Phi-4 14B

$0per month

~$10/month electricity. One-time setup.

Run Phi-4 14B on your own hardware.

Book a consultation. We'll configure this model — and the rest of your stack — in one day.