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text model · Qwen3.6 · Windows

Can I run Qwen3.6 27B on Nvidia GeForce RTX 4090 (24GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated ~39 tok/s est.

Yes. Qwen3.6 27B runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~18.9 GB of ~23 GB usable).

Needs ~18.9 GB Device usable ~23 GB

Runs at Q4_K_M using ~18.9 GB of ~23 GB usable.

That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 4090 (24GB) leaves ~4.1 GB of headroom.

Q4_K_M needed
~18.9 GB
Usable on device
~23 GB
Device memory
24 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~23 GB usable
Q2_K
~13.7 GB
Q3_K_M
~15.7 GB
Q4_K_M
~18.9 GB
Q5_K_M
~21.9 GB
Q6_K
~24.9 GB
Q8_0
~30.7 GB
FP16
~55.9 GB
The line marks Nvidia GeForce RTX 4090 (24GB)'s ~23 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~450 W
Electricity / 1M tokens
~$0.48
Pays for itself after
~79,950M tok

At ~$0.15/kWh and the estimated ~39 tok/s, a million generated tokens costs about $0.48 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,599 Nvidia GeForce RTX 4090 (24GB) pays for itself after roughly 79,950 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 qwen3.6:27b
llama.cpp
$ llama-cli -hf unsloth/Qwen3.6-27B-GGUF:Q4_K_M
LM Studio
$ lms get unsloth/Qwen3.6-27B-GGUF
Model Qwen3.6
Parameters
27.8B
Q4_K_M size
16.82 GB
Q8_0 size
28.6 GB
Context
256k
Ollama tag
qwen3.6:27b
Full Qwen3.6 27B requirements →
Device Windows
Memory
24 GB vram
Usable for weights
~23 GB
Power draw
~450 W
Best runtime
vLLM (Linux) / Ollama (CUDA)
Best models for Nvidia GeForce RTX 4090 (24GB) →

You could also run

Run Qwen3.6 27B on other hardware

FAQ

Can Nvidia GeForce RTX 4090 (24GB) run Qwen3.6 27B?

Yes. Qwen3.6 27B runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~18.9 GB of ~23 GB usable).

How much memory does Qwen3.6 27B need?

Nvidia GeForce RTX 4090 (24GB) has room to spare. At Q4_K_M the weights are ~16.82 GB; with KV cache and runtime overhead, budget ~18.9 GB at a 4k context.

What is the best tool to run Qwen3.6 27B 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.