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text model · Qwen3 · Windows

Can I run Qwen3 1.7B on Nvidia GeForce RTX 4060 Ti (16GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated ~146 tok/s est.

Yes. Qwen3 1.7B runs on Nvidia GeForce RTX 4060 Ti (16GB) at Q4_K_M (~2.4 GB of ~15 GB usable).

Needs ~2.4 GB Device usable ~15 GB

Runs at Q4_K_M using ~2.4 GB of ~15 GB usable. You have room for FP16 for higher quality.

That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 4060 Ti (16GB) leaves ~12.6 GB of headroom, room to step up to FP16 for higher quality.

Q4_K_M needed
~2.4 GB
Usable on device
~15 GB
Device memory
16 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~15 GB usable
Q2_K
~1.8 GB
Q3_K_M
~1.9 GB
Q4_K_M
~2.4 GB
Q5_K_M
~2.3 GB
Q6_K
~2.5 GB
Q8_0
~3.3 GB
FP16
~4.5 GB
The line marks Nvidia GeForce RTX 4060 Ti (16GB)'s ~15 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~165 W
Electricity / 1M tokens
~$0.05
Pays for itself after
~1,109M tok

At ~$0.15/kWh and the estimated ~146 tok/s, a million generated tokens costs about $0.05 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$499 Nvidia GeForce RTX 4060 Ti (16GB) pays for itself after roughly 1,109 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 qwen3:1.7b
llama.cpp
$ llama-cli -hf bartowski/Qwen_Qwen3-1.7B-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/Qwen_Qwen3-1.7B-GGUF
Model Qwen3
Parameters
1.7B
Q4_K_M size
1.28 GB
Q8_0 size
2.17 GB
Context
32k
Ollama tag
qwen3:1.7b
Full Qwen3 1.7B requirements →
Device Windows
Memory
16 GB vram
Usable for weights
~15 GB
Power draw
~165 W
Best runtime
Ollama (CUDA) / llama.cpp CUDA
Best models for Nvidia GeForce RTX 4060 Ti (16GB) →

You could also run

Run Qwen3 1.7B on other hardware

FAQ

Can Nvidia GeForce RTX 4060 Ti (16GB) run Qwen3 1.7B?

Yes. Qwen3 1.7B runs on Nvidia GeForce RTX 4060 Ti (16GB) at Q4_K_M (~2.4 GB of ~15 GB usable).

How much memory does Qwen3 1.7B need?

Nvidia GeForce RTX 4060 Ti (16GB) has room to spare. At Q4_K_M the weights are ~1.28 GB; with KV cache and runtime overhead, budget ~2.4 GB at a 4k context.

What is the best tool to run Qwen3 1.7B 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.