What GPU do I need to run mistralai/Mixtral-8x7B-Instruct-v0.1?
46.7B parameters, published in BF16. View on Hugging Face Full specs & deploy guide
Set up Mixtral-8x7B-Instruct-v0.1Mixtral-8x7B-Instruct-v0.1 is published by mistralai on Hugging Face, with 213,678 downloads and 4,756 likes to date. It's a MixtralForCausalLM 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.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| BF16 | 87.0 GB | 104.4 GB | RTX 3090 | 5 | $0.735/hr |
| FP8 (quantized) | 43.5 GB | 52.2 GB | RTX PRO 6000 | 1 | $1.64/hr |
| cheaper alt. | RTX 4000 SFF Ada | 3 | $0.540/hr | ||
| INT4 (quantized) | 21.7 GB | 26.1 GB | RTX A6000 | 1 | $0.330/hr |
| cheaper alt. | RTX A4000 | 2 | $0.226/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 Mixtral-8x7B-Instruct-v0.1 at its published (BF16) precision: 5× RTX 3090, at $0.147/hr per GPU ($0.735/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Mixtral-8x7B-Instruct-v0.1: common questions
Can Mixtral-8x7B-Instruct-v0.1 run on a single GPU?
No. At BF16 it needs 104.4 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest capable card in the live feed is a 24.0 GB RTX 3090, and it takes 5 of them.
How many GPUs do I need to run Mixtral-8x7B-Instruct-v0.1?
5 at BF16. It needs 104.4 GB of VRAM and the cheapest capable live offer is a 24.0 GB RTX 3090, so 5 of them come to $0.735/hr in total.
What is the least VRAM Mixtral-8x7B-Instruct-v0.1 can run in?
26.1 GB, at INT4 (quantized), which fits a 32 GB card, against 104.4 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 Mixtral-8x7B-Instruct-v0.1 lower the GPU bill?
Yes. At BF16 the cheapest live fit is 5 RTX 3090 cards at $0.735/hr. At INT4 (quantized) it drops to one RTX A6000 at $0.330/hr, provided a quantized checkpoint exists for it.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More mistralai models
- Voxtral-Mini-4B-Realtime-2602 (4.4B, BF16)
- Mistral-7B-Instruct-v0.2 (7.2B, BF16)
- Mistral-7B-v0.1 (7.2B, BF16)
- Mistral-7B-Instruct-v0.1 (7.2B, BF16)
- Mistral-Small-24B-Instruct-2501 (23.6B, BF16)
- bert-base-uncased (110M, F32)
