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OPEN MODELS / Language models (LLM)

Run Mistral-Small-24B-Instruct-2501-quantized.w8a8 on a cloud GPU

Mistral-Small-24B-Instruct-2501-quantized.w8a8 is a Language models (LLM) model by RedHatAI. See how much GPU memory it needs, which GPUs it fits on today and what it costs to run it yourself, billed per second.

Rent Q RTX 8000 from $0.48/hr
Parameters
24B
GPU memory needed
≈ 30 GB
License
apache-2.0
Downloads
14,185
Updated Jun 9, 2026

GPUs it fits on today

Our estimate is about 30 GB for inference with I8 weights, including working memory. Real use depends on resolution, batch size and context length. With 4-bit quantization it needs about 18 GB.

GPUMemoryPer hour10 hours
Q RTX 800045 GB$0.48$4.80Rent
CMP 170HX64 GB$0.62$6.20Rent
RTX 5000Ada32 GB$0.69$6.90Rent
GB10119 GB$0.71$7.10Rent
A100 SXM480 GB$0.72$7.20Rent

Live starting prices from our catalog. You pay per second while the machine runs.

How to run Mistral-Small-24B-Instruct-2501-quantized.w8a8

  1. 01

    Rent a GPU

    Pick one of the GPUs above. Billing is per second; stop the machine and you stop paying.

  2. 02

    Open a terminal or Jupyter

    Connect over SSH or open Jupyter in your browser. PyTorch and CUDA are ready to use.

  3. 03

    Download and run the model

    Run the commands below. The weights download straight from Hugging Face to your machine.

pip install -U vllm
vllm serve RedHatAI/Mistral-Small-24B-Instruct-2501-quantized.w8a8 --host 0.0.0.0 --port 8000

Why run it yourself?

Your own LLM server has no per-token bill and no rate limit, and your data stays private. Pick a GPU by memory and serve the model with vLLM.

Questions

How much GPU memory does Mistral-Small-24B-Instruct-2501-quantized.w8a8 need?
By our estimate about 30 GB for inference (24B parameters). Higher resolution, longer context or bigger batches need more.
How much does it cost to run Mistral-Small-24B-Instruct-2501-quantized.w8a8?
From $0.48 per hour on Q RTX 8000, billed per second. Ten hours cost about $4.80.
Do I need a subscription?
No. You pay only for the time your machine runs, from your USD balance. Stop it whenever you are done.

Try it on your own GPU in minutes

Pick a GPU, open Jupyter or SSH and run any open model. You pay per second and can stop anytime; no subscription, no setup fee.

  • Per-second billing in USD
  • PyTorch and CUDA ready in minutes
  • Rent from ChatGPT or Claude too

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