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text model · Qwen2.5-Coder · Windows

Can I run Qwen2.5 Coder 32B on 16GB RAM Laptop (CPU/iGPU only)?

Compatibility verdict VRAM threshold engine
No, not enough memory would not load

No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but 16GB RAM Laptop (CPU/iGPU only) only has ~12 GB usable.

Needs ~20.7 GB Device usable ~12 GB

Needs ~20.7 GB even at Q4_K_M, but only ~12 GB is usable.

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

The gap is about 8.7 GB: Qwen2.5 Coder 32B needs roughly 20.7 GB at Q4_K_M and 16GB RAM Laptop (CPU/iGPU only) leaves only about 12 GB usable for a model. The lightest tracked hardware that runs Qwen2.5 Coder 32B is the Nvidia GeForce RTX 4090 (24GB) at 24 GB. See Qwen2.5 Coder 32B on Nvidia GeForce RTX 4090 (24GB).

Q4_K_M needed
~20.7 GB
Usable on device
~12 GB
Device memory
16 GB
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Which quant fits

Quant ladder vs ~12 GB usable
Q2_K
~15.6 GB
Q3_K_M
~17.8 GB
Q4_K_M
~20.7 GB
Q5_K_M
~25 GB
Q6_K
~28.4 GB
Q8_0
~34.6 GB
FP16
~66.2 GB
The line marks 16GB RAM Laptop (CPU/iGPU only)'s ~12 GB budget; rungs past it are too large.
Model Qwen2.5-Coder
Parameters
32B
Q4_K_M size
18.49 GB
Q8_0 size
32.43 GB
Context
32k
Ollama tag
qwen2.5-coder:32b
Full Qwen2.5 Coder 32B requirements →
Device Windows
Memory
16 GB ram
Usable for weights
~12 GB
Power draw
~28 W
Best runtime
Ollama (llama.cpp backend)
Best models for 16GB RAM Laptop (CPU/iGPU only) →

What you can run instead

Run Qwen2.5 Coder 32B on other hardware

FAQ

Can 16GB RAM Laptop (CPU/iGPU only) run Qwen2.5 Coder 32B?

No. Qwen2.5 Coder 32B needs ~20.7 GB even at Q4_K_M, but 16GB RAM Laptop (CPU/iGPU only) only has ~12 GB usable.

How much memory does Qwen2.5 Coder 32B need?

16GB RAM Laptop (CPU/iGPU only) does not have enough memory. At Q4_K_M the weights are ~18.49 GB; with KV cache and runtime overhead, budget ~20.7 GB at a 4k context.

What is the best tool to run Qwen2.5 Coder 32B 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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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.