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text model · Command R · Windows

Can I run Command R 35B on Nvidia GeForce RTX 5090 (32GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs usable speed ~58 tok/s est.

Yes. Command R 35B runs on Nvidia GeForce RTX 5090 (32GB) at Q4_K_M (~22.3 GB of ~31 GB usable).

Needs ~22.3 GB Device usable ~31 GB

Runs at Q4_K_M using ~22.3 GB of ~31 GB usable.

That figure is at a 4k context and moves about ±15% as context length changes. Nvidia GeForce RTX 5090 (32GB) leaves ~8.7 GB of headroom.

Q4_K_M needed
~22.3 GB
Usable on device
~31 GB
Device memory
32 GB
Best quant
Q4_K_M
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Which quant fits

Quant ladder vs ~31 GB usable
Q2_K
~16.9 GB
Q3_K_M
~19.3 GB
Q4_K_M
~22.3 GB
Q5_K_M
~27.1 GB
Q6_K
~30.9 GB
Q8_0
~36.8 GB
FP16
~72.2 GB
The line marks Nvidia GeForce RTX 5090 (32GB)'s ~31 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~575 W
Electricity / 1M tokens
~$0.41
Pays for itself after
~22,211M tok

At ~$0.15/kWh and the estimated ~58 tok/s, a million generated tokens costs about $0.41 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,999 Nvidia GeForce RTX 5090 (32GB) pays for itself after roughly 22,211 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 command-r:35b
llama.cpp
$ llama-cli -hf bartowski/c4ai-command-r-v01-GGUF:Q4_K_M
LM Studio
$ lms get bartowski/c4ai-command-r-v01-GGUF
Model Command R
Parameters
35B
Q4_K_M size
20.05 GB
Q8_0 size
34.63 GB
Context
128k
Ollama tag
command-r:35b
Full Command R 35B requirements →
Device Windows
Memory
32 GB vram
Usable for weights
~31 GB
Power draw
~575 W
Best runtime
vLLM (Linux) / Ollama (CUDA)
Best models for Nvidia GeForce RTX 5090 (32GB) →

You could also run

Run Command R 35B on other hardware

FAQ

Can Nvidia GeForce RTX 5090 (32GB) run Command R 35B?

Yes. Command R 35B runs on Nvidia GeForce RTX 5090 (32GB) at Q4_K_M (~22.3 GB of ~31 GB usable).

How much memory does Command R 35B need?

Nvidia GeForce RTX 5090 (32GB) has room to spare. At Q4_K_M the weights are ~20.05 GB; with KV cache and runtime overhead, budget ~22.3 GB at a 4k context.

What is the best tool to run Command R 35B 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.