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
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.
| Precision | Weight size | Required VRAM | Cheapest live fit | GPUs needed | Est. $/hr (full fit) |
|---|---|---|---|---|---|
| FP8 (native) | 378.0 GB | 453.6 GB | RTX PRO 6000 | 5 | $8.20/hr |
| INT4 (quantized) | 189.0 GB | 226.8 GB | RTX A6000 | 5 | $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.
More NousResearch models
- Hermes-3-Llama-3.1-8B (8.0B, BF16)
- Meta-Llama-3.1-8B-Instruct (8.0B, BF16)
- Llama-2-7b-hf (6.7B, F16)
- Meta-Llama-3-8B-Instruct (8.0B, BF16)
- Meta-Llama-3-8B (8.0B, BF16)
- Llama-3.2-1B (1.2B, BF16)