text model · Phi-4 · Windows

Can I run Phi-4-reasoning on 8GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Phi-4-reasoning needs ~10.1 GB even at Q4_K_M, but 8GB RAM Laptop (CPU/iGPU only) only has ~5 GB usable.

Needs ~10.1 GB Device usable ~5 GB

Needs ~10.1 GB even at Q4_K_M, but only ~5 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 5.1 GB: Phi-4-reasoning needs roughly 10.1 GB at Q4_K_M and 8GB RAM Laptop (CPU/iGPU only) leaves only about 5 GB usable for a model. The lightest tracked hardware that runs Phi-4-reasoning is the Nvidia GeForce RTX 3060 (12GB) at 12 GB. See Phi-4-reasoning on Nvidia GeForce RTX 3060 (12GB).

Q4_K_M needed: ~10.1 GB
Usable on device: ~5 GB
Device memory: 8 GB

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Which quant fits

Quant ladder vs ~5 GB usable

Q2_K

~7.6 GB

Q3_K_M

~8.5 GB

Q4_K_M

~10.1 GB

Q5_K_M

~11.7 GB

Q6_K

~13.2 GB

Q8_0

~16.2 GB

FP16

~31 GB

The line marks 8GB RAM Laptop (CPU/iGPU only)'s ~5 GB budget; rungs past it are too large.

Model Phi-4

Parameters: 14B
Q4_K_M size: 8.43 GB
Q8_0 size: 14.51 GB
Context: 32k
Ollama tag: phi4-reasoning:14b

Full Phi-4-reasoning requirements →

Device Windows

Memory: 8 GB ram
Usable for weights: ~5 GB
Power draw: ~15 W
Best runtime: Ollama (llama.cpp backend)

Best models for 8GB RAM Laptop (CPU/iGPU only) →

What you can run instead

Run Phi-4-reasoning on other hardware

Nvidia GeForce RTX 3060 (12GB)Nvidia GeForce RTX 4070 (12GB)Apple M2 (16GB)Apple M4 (16GB)Nvidia GeForce RTX 4060 Ti (16GB)Nvidia GeForce RTX 4080 (16GB)

FAQ

Can 8GB RAM Laptop (CPU/iGPU only) run Phi-4-reasoning?

No. Phi-4-reasoning needs ~10.1 GB even at Q4_K_M, but 8GB RAM Laptop (CPU/iGPU only) only has ~5 GB usable.

How much memory does Phi-4-reasoning need?

8GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~8.43 GB; with KV cache and runtime overhead, budget ~10.1 GB at a 4k context.

What is the best tool to run Phi-4-reasoning 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.

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Markdown

[![Phi-4-reasoning on 8GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/badge/phi-4-reasoning/laptop-8gb.svg)](https://localmodel.run/can-i-run/phi-4-reasoning/laptop-8gb)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.