text model · Olmo · Windows

Can I run Olmo 3.1 32B Instruct on Nvidia GeForce RTX 4090 (24GB)?

Compatibility verdict VRAM threshold engine

Yes, it runs GPU accelerated ~36 tok/s est.

Yes. Olmo 3.1 32B Instruct runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~20.3 GB of ~23 GB usable).

Needs ~20.3 GB Device usable ~23 GB

Runs at Q4_K_M using ~20.3 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 ~2.7 GB of headroom.

Q4_K_M needed: ~20.3 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

~15.6 GB

Q3_K_M

~17.8 GB

Q4_K_M

~20.3 GB

Q5_K_M

~25 GB

Q6_K

~28.4 GB

Q8_0

~34.1 GB

FP16

~66.2 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: ~$0.52

At ~$0.15/kWh and the estimated ~36 tok/s, a million generated tokens costs about $0.52 in electricity. 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 olmo-3.1:32b-instruct

llama.cpp

$ llama-cli -hf bartowski/allenai_Olmo-3.1-32B-Instruct-GGUF:Q4_K_M

LM Studio

$ lms get bartowski/allenai_Olmo-3.1-32B-Instruct-GGUF

Model Olmo

Parameters: 32B
Q4_K_M size: 18.14 GB
Q8_0 size: 31.9 GB
Context: 64k
Ollama tag: olmo-3.1:32b-instruct

Full Olmo 3.1 32B Instruct 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 Olmo 3.1 32B Instruct on other hardware

Nvidia GeForce RTX 3090 (24GB)AMD Radeon RX 7900 XTX (24GB)Nvidia GeForce RTX 5090 (32GB)32GB RAM Laptop (CPU/iGPU only)Apple M5 (32GB)Apple M4 Pro (48GB)

FAQ

Can Nvidia GeForce RTX 4090 (24GB) run Olmo 3.1 32B Instruct?

Yes. Olmo 3.1 32B Instruct runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~20.3 GB of ~23 GB usable).

How much memory does Olmo 3.1 32B Instruct need?

Nvidia GeForce RTX 4090 (24GB) has room to spare. At Q4_K_M the weights are ~18.14 GB; with KV cache and runtime overhead, budget ~20.3 GB at a 4k context.

What is the best tool to run Olmo 3.1 32B Instruct 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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Markdown

[![Olmo 3.1 32B Instruct on Nvidia GeForce RTX 4090 (24GB)](https://localmodel.run/badge/olmo-3.1-32b-instruct/nvidia-rtx-4090-24gb.svg)](https://localmodel.run/can-i-run/olmo-3.1-32b-instruct/nvidia-rtx-4090-24gb)

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.