What GPU do I need to run NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO?
46.7B parameters, published in BF16. View on Hugging Face
Nous-Hermes-2-Mixtral-8x7B-DPO is published by NousResearch on Hugging Face, with 19,587 downloads and 459 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.
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 caveat: requires a quantized checkpoint actually published for this model, check its Hugging Face page before relying on this row.
Cheapest way to run Nous-Hermes-2-Mixtral-8x7B-DPO at its published (BF16) precision: 7× RTX 5060 Ti on simplepod, at $0.100/hr per GPU ($0.700/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.
Weight-to-VRAM math, the fit rules, and how live prices are normalized: full methodology.
More NousResearch models
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- Meta-Llama-3-8B-Instruct (8.0B, BF16)
- Meta-Llama-3-8B (8.0B, BF16)
- Llama-3.2-1B (1.2B, BF16)
