What GPU do I need to run NousResearch/Hermes-3-Llama-3.1-405B-FP8?

405.9B parameters, published in F8_E4M3. View on Hugging Face Full specs & deploy guide

405.9B
Parameters
F8_E4M3
Native precision
LlamaForCausalLM
Architecture
text-generation
Pipeline

Hermes-3-Llama-3.1-405B-FP8 is published by NousResearch on Hugging Face, with 150 downloads and 29 likes to date. It's a LlamaForCausalLM model built for text-generation, published natively in F8_E4M3.

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)
FP8 (native)378.0 GB453.6 GBRTX PRO 60005$8.20/hr
INT4 (quantized)189.0 GB226.8 GBRTX A60005$1.65/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 Hermes-3-Llama-3.1-405B-FP8 at its published (F8_E4M3) precision: 5× RTX PRO 6000, at $1.64/hr per GPU ($8.20/hr total). Quantizing to FP8 or INT4 (rows above) can cost less, but requires a compatible quantized checkpoint to exist for this model.

Hermes-3-Llama-3.1-405B-FP8: common questions

Can Hermes-3-Llama-3.1-405B-FP8 run on a single GPU?

No. At FP8 (native) it needs 453.6 GB of VRAM, more than a single 32 GB desktop card holds. The cheapest capable card in the live feed is a 96.0 GB RTX PRO 6000, and it takes 5 of them.

Is Hermes-3-Llama-3.1-405B-FP8 already quantized?

Yes. It is published in FP8, one byte per parameter, so the 453.6 GB figure is already a quantized footprint rather than a full-precision one. Only INT4 goes below it, at 226.8 GB. A GPU without FP8 tensor cores cannot run it as published, which is why cards here are matched on precision support and not on VRAM alone.

How many GPUs do I need to run Hermes-3-Llama-3.1-405B-FP8?

5 at FP8 (native). It needs 453.6 GB of VRAM and the cheapest capable live offer is a 96.0 GB RTX PRO 6000, so 5 of them come to $8.20/hr in total.

Does quantizing Hermes-3-Llama-3.1-405B-FP8 lower the GPU bill?

Yes. At FP8 (native) the cheapest live fit is 5 RTX PRO 6000 cards at $8.20/hr. At INT4 (quantized) it drops to 5 RTX A6000 cards at $1.65/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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