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text model · Mistral · Windows

Can I run Devstral Small on Nvidia GeForce RTX 3090 (24GB)?

Compatibility verdict VRAM threshold engine
Yes, it runs GPU accelerated ~46 tok/s est.

Yes. Devstral Small runs on Nvidia GeForce RTX 3090 (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 3090 (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
~49.2 GB
The line marks Nvidia GeForce RTX 3090 (24GB)'s ~23 GB budget; rungs past it are too large.

Running cost · estimate

Power & economics est.
Power draw
~350 W
Electricity / 1M tokens
~$0.32
Pays for itself after
~8,328M tok

At ~$0.15/kWh and the estimated ~46 tok/s, a million generated tokens costs about $0.32 in electricity. Versus a hosted API at ~$0.5 per million tokens, the ~$1,499 Nvidia GeForce RTX 3090 (24GB) pays for itself after roughly 8,328 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:24b
llama.cpp
$ llama-cli -hf mistralai/Devstral-Small-2507_gguf:Q4_K_M
LM Studio
$ lms get mistralai/Devstral-Small-2507_gguf
Model Mistral
Parameters
24B
Q4_K_M size
13.35 GB
Q8_0 size
23.33 GB
Context
128k
Ollama tag
devstral:24b
Full Devstral Small requirements →
Device Windows
Memory
24 GB vram
Usable for weights
~23 GB
Power draw
~350 W
Best runtime
vLLM (Linux) / Ollama (CUDA)
Best models for Nvidia GeForce RTX 3090 (24GB) →

You could also run

Run Devstral Small on other hardware

FAQ

Can Nvidia GeForce RTX 3090 (24GB) run Devstral Small?

Yes. Devstral Small runs on Nvidia GeForce RTX 3090 (24GB) at Q4_K_M (~15.4 GB of ~23 GB usable).

How much memory does Devstral Small need?

Nvidia GeForce RTX 3090 (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 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.