text model · Mistral · Windows

Can I run Devstral Small 2 24B on Nvidia GeForce RTX 4090 (24GB)?

Compatibility verdict VRAM threshold engine

Yes, it runs GPU accelerated ~49 tok/s est.

Yes. Devstral Small 2 24B runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~15.4 GB of ~23 GB usable).

Needs ~15.4 GB Device usable ~23 GB

Runs at Q4_K_M using ~15.4 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 ~7.6 GB of headroom.

Q4_K_M needed: ~15.4 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

~12.1 GB

Q3_K_M

~13.7 GB

Q4_K_M

~15.4 GB

Q5_K_M

~19.1 GB

Q6_K

~21.7 GB

Q8_0

~25.3 GB

FP16

~50 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: ~$0.38
Pays for itself after: ~13,325M tok

At ~$0.15/kWh and the estimated ~49 tok/s, a million generated tokens costs about $0.38 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 13,325 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 devstral-small-2:24b

llama.cpp

$ llama-cli -hf unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF:Q4_K_M

LM Studio

$ lms get unsloth/Devstral-Small-2-24B-Instruct-2512-GGUF

Model Mistral

Parameters: 24B
Q4_K_M size: 13.35 GB
Q8_0 size: 23.33 GB
Context: 384k
Ollama tag: devstral-small-2:24b

Full Devstral Small 2 24B 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 Devstral Small 2 24B on other hardware

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

FAQ

Can Nvidia GeForce RTX 4090 (24GB) run Devstral Small 2 24B?

Yes. Devstral Small 2 24B runs on Nvidia GeForce RTX 4090 (24GB) at Q4_K_M (~15.4 GB of ~23 GB usable).

How much memory does Devstral Small 2 24B need?

Nvidia GeForce RTX 4090 (24GB) has room to spare. At Q4_K_M the weights are ~13.35 GB; with KV cache and runtime overhead, budget ~15.4 GB at a 4k context.

What is the best tool to run Devstral Small 2 24B 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

[![Devstral Small 2 24B on Nvidia GeForce RTX 4090 (24GB)](https://localmodel.run/badge/devstral-small-2-24b/nvidia-rtx-4090-24gb.svg)](https://localmodel.run/can-i-run/devstral-small-2-24b/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.