text model · Qwen2.5 · Windows

Can I run Qwen2.5 72B on 32GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. Qwen2.5 72B needs ~50.2 GB even at Q4_K_M, but 32GB RAM Laptop (CPU/iGPU only) only has ~28 GB usable.

Needs ~50.2 GB Device usable ~28 GB

Needs ~50.2 GB even at Q4_K_M, but only ~28 GB is usable.

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

The gap is about 22.2 GB: Qwen2.5 72B needs roughly 50.2 GB at Q4_K_M and 32GB RAM Laptop (CPU/iGPU only) leaves only about 28 GB usable for a model. The lightest tracked hardware that runs Qwen2.5 72B is the Apple M4 Max (128GB) at 128 GB. See Qwen2.5 72B on Apple M4 Max (128GB).

Q4_K_M needed: ~50.2 GB
Usable on device: ~28 GB
Device memory: 32 GB

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Which quant fits

Quant ladder vs ~28 GB usable

Q2_K

~33 GB

Q3_K_M

~38 GB

Q4_K_M

~50.2 GB

Q5_K_M

~54.1 GB

Q6_K

~61.8 GB

Q8_0

~80.1 GB

FP16

~146.8 GB

The line marks 32GB RAM Laptop (CPU/iGPU only)'s ~28 GB budget; rungs past it are too large.

Model Qwen2.5

Parameters: 72B
Q4_K_M size: 47.42 GB
Q8_0 size: 77.26 GB
Context: 128k
Ollama tag: qwen2.5:72b

Full Qwen2.5 72B requirements →

Device Windows

Memory: 32 GB ram
Usable for weights: ~28 GB
Power draw: ~28 W
Best runtime: Ollama (llama.cpp backend)

Best models for 32GB RAM Laptop (CPU/iGPU only) →

What you can run instead

Run Qwen2.5 72B on other hardware

Apple M4 Max (128GB)AMD Ryzen AI Halo (128GB)Apple M5 Max (128GB)Apple M3 Ultra (256GB)

FAQ

Can 32GB RAM Laptop (CPU/iGPU only) run Qwen2.5 72B?

No. Qwen2.5 72B needs ~50.2 GB even at Q4_K_M, but 32GB RAM Laptop (CPU/iGPU only) only has ~28 GB usable.

How much memory does Qwen2.5 72B need?

32GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~47.42 GB; with KV cache and runtime overhead, budget ~50.2 GB at a 4k context.

What is the best tool to run Qwen2.5 72B 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

[![Qwen2.5 72B on 32GB RAM Laptop (CPU/iGPU only)](https://localmodel.run/badge/qwen2.5-72b/laptop-32gb.svg)](https://localmodel.run/can-i-run/qwen2.5-72b/laptop-32gb)

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.