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text model · Qwen2.5-Coder · Windows

Can I run Qwen2.5 Coder 14B on Nvidia GeForce RTX 3060 (12GB)?

Compatibility verdict VRAM threshold engine
Yes, but tight GPU accelerated ~28 tok/s est.

Yes. Qwen2.5 Coder 14B runs on Nvidia GeForce RTX 3060 (12GB) at Q4_K_M (~10.1 GB of ~11 GB usable).

Needs ~10.1 GB Device usable ~11 GB

Fits at Q4_K_M (~10.1 GB of ~11 GB usable) but with little headroom. Close other apps; a smaller context frees a few hundred MB.

That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 3060 (12GB) leaves ~0.9 GB of headroom.

Q4_K_M needed
~10.1 GB
Usable on device
~11 GB
Device memory
12 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~11 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
~16.3 GB
FP16
~29.7 GB
The line marks Nvidia GeForce RTX 3060 (12GB)'s ~11 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~170 W
Electricity / 1M tokens
~$0.25
Pays for itself after
~1,316M tok

At ~$0.15/kWh and the estimated ~28 tok/s, a million generated tokens costs about $0.25 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$329 Nvidia GeForce RTX 3060 (12GB) pays for itself after roughly 1,316 million tokens, so local hardware is mostly a fixed cost, not a per-token one. TDP is the peak draw, so this is an upper bound. Assumptions.

Run it

Install commands Windows

Pick your tool. All 3 load the same Q4_K_M weights.

Ollama
$ ollama run qwen2.5-coder:14b
llama.cpp
$ llama-cli -hf bartowski/Qwen2.5-Coder-14B-Instruct-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/Qwen2.5-Coder-14B-Instruct-GGUF
Model Qwen2.5-Coder
Parameters
14B
Q4_K_M size
8.37 GB
Q8_0 size
14.62 GB
Context
32k
Ollama tag
qwen2.5-coder:14b
Full Qwen2.5 Coder 14B requirements →
Device Windows
Memory
12 GB vram
Usable for weights
~11 GB
Power draw
~170 W
Best runtime
Ollama (CUDA) / llama.cpp CUDA
Best models for Nvidia GeForce RTX 3060 (12GB) →

You could also run

Run Qwen2.5 Coder 14B on other hardware

FAQ

Can Nvidia GeForce RTX 3060 (12GB) run Qwen2.5 Coder 14B?

Yes. Qwen2.5 Coder 14B runs on Nvidia GeForce RTX 3060 (12GB) at Q4_K_M (~10.1 GB of ~11 GB usable).

How much memory does Qwen2.5 Coder 14B need?

It is a tight fit on Nvidia GeForce RTX 3060 (12GB). At Q4_K_M the weights are ~8.37 GB; with KV cache and runtime overhead, budget ~10.1 GB at a 4k context.

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

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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.