Phi-4 14B
Phi-4 14B loads in 11.5 GB at Q4_K_M, comfortably from 24 GB of memory — Macs included, starting at the MacBook Air M5 24GB. Below is the memory math we ran for it, the cheapest card that fits, and the fastest machine we track.
How much memory does Phi-4 14B need?
Phi-4 14B is a 14B dense model built for coding, quality. The weights alone take 11.5 GB at Q4_K_M; add context and the OS, and it belongs in the 24 GB memory class. Every number below comes from the ModelFit engine — speeds are estimates, labeled est., because we do not benchmark hardware ourselves.
KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).
Which machines run Phi-4 14B?
Verdicts come from the same engine that powers our fit checker — memory capacity first, bandwidth for speed. How we compute these numbers · Hugging Face model card
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Frequently asked questions
How much memory does Phi-4 14B need?
11.5 GB for the Q4_K_M weights, plus ~3.0 GB of KV-cache at 16k context — about 14.5 GB total. Comfortable from 24 GB of VRAM or unified memory.
Does Phi-4 14B run on a Mac?
Yes — from the MacBook Air M5 24GB (~14 tok/s est.). Unified memory means the RAM budget is the only limit.
What is the cheapest GPU for Phi-4 14B?
The AMD Radeon RX 7900 XT is the cheapest tracked card that runs Phi-4 14B comfortably — ~46 tok/s est. at ~$550 used.
Which Phi-4 14B quant should I pick?
The tracked Q4_K_M build at 11.5 GB is the one we recommend for most machines. Every published build, ranked by real GGUF file size rather than a formula, is on the quant comparison page linked below.
Cite this page
ModelFit: Phi-4 14B — specs, memory math and hardware verdicts. https://modelfit.io/models/phi4-14b/ (dataset updated 2026-09-03, CC BY 4.0).