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text model · phi · Windows

Can I run Phi-4 14B on 16GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine
Yes, but tightslow on this hardware

Yes. Phi-4 14B runs on 16GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~10.8 GB of ~12 GB usable).

Needs ~10.8 GB Device usable ~12 GB

Fits at Q4_K_M (~10.8 GB of ~12 GB usable) but with little headroom, close other apps.

Q4_K_M needed
~10.8 GB
Usable on device
~12 GB
Device memory
16 GB
Best quant
Q4_K_M

Run it

Install commands Windows

Pick your tool. All three load the same Q4_K_M weights.

Ollama
$ ollama run phi4:14b
llama.cpp
$ llama-cli -hf bartowski/phi-4-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/phi-4-GGUF

AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

Model phi
Parameters
14B
Q4_K_M size
9.05 GB
Q8_0 size
15.58 GB
Context
16k
Ollama tag
phi4:14b
Full Phi-4 14B requirements →
Device Windows
Memory
16 GB ram
Usable for weights
~12 GB
Best runtime
Ollama (llama.cpp backend)
Best models for 16GB RAM Laptop (CPU/iGPU only) →

You could also run

Run Phi-4 14B on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)iPad Pro M4 (16GB, 1TB/2TB config)Samsung Galaxy S25 Ultra (16GB, 1TB config only)

FAQ

Can 16GB RAM Laptop (CPU/iGPU only) run Phi-4 14B?

Yes. Phi-4 14B runs on 16GB RAM Laptop (CPU/iGPU only) at Q4_K_M (~10.8 GB of ~12 GB usable).

How much memory does Phi-4 14B need?

It is a tight fit on 16GB RAM Laptop (CPU/iGPU only). At Q4_K_M the weights are ~9.05 GB; with KV cache and runtime overhead, budget ~10.8 GB at a 4k context.

What is the best tool to run Phi-4 14B on Windows?

LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.

Sources

Memory figures are estimates. See methodology.