What GPU do I need to run mistralai/Mistral-Small-24B-Instruct-2501?

23.6B parameters, published in BF16. View on Hugging Face Full specs & deploy guide

23.6B
Parameters
BF16
Native precision
MistralForCausalLM
Architecture
text-generation
Pipeline

Mistral-Small-24B-Instruct-2501 is published by mistralai on Hugging Face, with 50,489 downloads and 970 likes to date. It's a MistralForCausalLM model built for text-generation, published natively in BF16.

VRAM required & cheapest live GPU fit

Required VRAM = weight size at each precision, plus a fixed overhead for KV-cache, activations, and fragmentation. Full formula and assumptions: methodology.

PrecisionWeight sizeRequired VRAMCheapest live fitGPUs neededEst. $/hr (full fit)
BF1643.9 GB52.7 GBA1001$0.851/hr
cheaper alt.RTX 30903$0.441/hr
FP8 (quantized)22.0 GB26.3 GBRTX 4080 Super1$0.383/hr
cheaper alt.RTX 40802$0.315/hr
INT4 (quantized)11.0 GB13.2 GBRTX A40001$0.113/hr

A GPU is only matched to a row if its hardware supports that precision, and the primary recommendation is always a single-GPU fit when one exists.

INT4 requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.

Cheapest way to run Mistral-Small-24B-Instruct-2501 at its published (BF16) precision: 1× A100, at $0.851/hr per GPU ($0.851/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Mistral-Small-24B-Instruct-2501: common questions

Can Mistral-Small-24B-Instruct-2501 run on a single GPU?

Yes, but not on a desktop card. At BF16 it needs 52.7 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest live single-card fit is a 80.0 GB A100 at $0.851/hr.

What is the least VRAM Mistral-Small-24B-Instruct-2501 can run in?

13.2 GB, at INT4 (quantized), which fits a 16 GB card, against 52.7 GB at BF16. That row assumes an INT4 checkpoint has actually been published for this model, so check its Hugging Face page before planning around it.

Does quantizing Mistral-Small-24B-Instruct-2501 lower the GPU bill?

Yes. At BF16 the cheapest live fit is one A100 at $0.851/hr. At INT4 (quantized) it drops to one RTX A4000 at $0.113/hr, provided a quantized checkpoint exists for it.

Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.

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