Hermes 3 405B TPS calculator

Open weights Nous Research 405B parameters August 2024

Each card below is assessed against this model at the context length and minimum quality you choose. Speed is an estimate for a single request, calculated from the card's memory bandwidth and the size of the model once compressed.

Calculated for this model

4 of 818 cards that can run it

Smallest card that fits

Radeon Instinct MI325X

256 GB · IQ4_XS · 12.0 tok/s

Fastest card

B300

19.3 tok/s · 288 GB

Which GPUs can run Hermes 3 405B?

Set the inputs, read the answer

A longer conversation needs more memory, which can push this model off smaller cards.

Hides cards that would only fit the model by compressing it below this point.

4 cards match

Calculating
Needs Quantisation Fit
19.3 tok/s

12–31 · low confidence

B300 NVIDIA 288 GB 8,000 GB/s Sep 2025 245.7 GB Q4_K_M Tight
15.4 tok/s

9–25 · low confidence

Radeon Instinct MI350X AMD 288 GB 8,190 GB/s Jan 2025 245.7 GB Q4_K_M Tight
15.4 tok/s

9–25 · low confidence

Radeon Instinct MI355X AMD 288 GB 8,190 GB/s Jan 2025 245.7 GB Q4_K_M Tight
12.0 tok/s

7–19 · low confidence

Radeon Instinct MI325X AMD 256 GB 6,000 GB/s Oct 2024 222.1 GB IQ4_XS Tight

Speeds are estimates for a single request — one conversation at a time — calculated from memory bandwidth, model size and quantisation. Real throughput varies with the inference runtime and its version. Figures published by hardware vendors measure many simultaneous requests and are much higher.

On record

Full specification

Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.

Origin

Who built this model, where, and when it was published.

Organisation
Nous Research
Organisation type
Industry
Country
United States of America
Published
14 August 2024
Authors
teknium, Jeffrey Quesnelle, Chen Guang

What it does

The problem areas the model was built for. A model can carry several of each.

Domain
Language
Task
Language modeling/generation, Chat, Question answering
Base model
Llama 3.1-405B

Size

How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.

Parameters
405B

405B

Training data
270,000,000 tokens

390M tokens (Table 1)

Epochs
4

Training compute

The arithmetic performed to train the model, measured in floating-point operations. It is a measure of what the training run cost, not of how fast the finished model answers you.

How it was established
Hardware,Operation counting
Fine-tuning compute
2.9 × 10²¹ FLOP

6 FLOP / parameter / token * 405*10^9 parameters * 390*10^6 tokens * 4 epochs = 3.7908e+21 FLOP 989500000000000 FLOP / GPU / sec * 2086 GPU-hours * 3600 sec / hour * 0.3 [assumed utilization] = 2.2292248e+21 FLOP sqrt(2.2292248e+21*3.7908e+21) = 2.9069822e+21

The training run

What it physically took to train: which chips, how many, for how long, and what that drew from the wall.

Training hardware
NVIDIA H100 SXM5 80GB
Chips used
128
Chip-hours
2,086
Power draw
176.7 kW

Availability

Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.

Weights
Open — downloadable
Model access
Open weights (restricted use)
Training code
Unreleased

Llama license https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-405B

Hugging Face
NousResearch

How it is classified

Labels the source dataset applies when tracking notable models, and how confident it is in the entry.

Record confidence
Confident

Sources

Where this record came from and when it was last checked.

Reference
Hermes 3 Technical Report
Last updated
28 November 2025

The extremes

The ten fastest GPUs for Hermes 3 405B

Ranked by estimated tokens per second, newest card first where speeds tie. Because generation is bound by memory bandwidth, this ordering follows bandwidth rather than any gaming benchmark.

  1. 01 B300 288 GB · 8,000 GB/s · Q4_K_M 19.3 tok/s
  2. 02 Radeon Instinct MI350X 288 GB · 8,190 GB/s · Q4_K_M 15.4 tok/s
  3. 03 Radeon Instinct MI355X 288 GB · 8,190 GB/s · Q4_K_M 15.4 tok/s
  4. 04 Radeon Instinct MI325X 256 GB · 6,000 GB/s · IQ4_XS 12.0 tok/s

What the numbers mean

Hardware requirements in practice

Minimum card

Radeon Instinct MI325X

Memory needed

222.1 GB

Fastest

19.3 tok/s

At 405B parameters, Hermes 3 405B is beyond what any single graphics card holds. Running it means either splitting it across several cards or renting hardware built for the job — 4 of the cards we track can hold it on their own, and all of them are datacentre parts.

The entry point is the Radeon Instinct MI325X: 256 GB of memory, IQ4_XS compression, roughly 12.0 tokens per second.

The quickest result comes from a B300 at around 19.3 tokens per second — its 8,000 GB/s of bandwidth is what buys that.

Background

Hermes 3 405B was published by Nous Research, in United States of America, in August 2024. It comes out of industry.

It works in Language, and is recorded as doing language modeling/generation, Chat, Question answering.

Its starting point was Llama 3.1-405B — most models at this scale are adapted from an existing base rather than built from nothing.

The weights are published, so it can be downloaded and run on your own hardware indefinitely, offline, with no account attached. It is published under the NousResearch organisation on Hugging Face.

Reading the throughput figures

Across every card that can run it, the middle of the range is about 15.4 tokens per second, and 4 of them clear the ten tokens per second that roughly matches reading speed.

Being dense, it reads all of itself per token, which is why the ordering by speed below follows the ordering by memory bandwidth so closely.

Its internal architecture is not on file, so memory is approximated from the parameter count and marked accordingly. Expect the real figure to differ, more so at long context.

How it was trained

The training set ran to roughly 270,000,000 tokens.

Step by step

How to choose a GPU for Hermes 3 405B

The table above has already assessed every card we hold specifications for against this model. Getting to your answer takes six steps.

  1. 01

    Read the memory figure first

    Look at what Hermes 3 405B actually needs — around 222.1 GB at IQ4_XS. No amount of processing power compensates for a card that cannot hold it.

  2. 02

    Match the context to your actual use

    The conversation occupies memory too, and grows as it goes. Set the slider to the length you expect: at long context Hermes 3 405B can slip off a card that handles short questions easily.

  3. 03

    Choose how far you will compress it

    Each card runs the least-compressed copy it can hold — IQ4_XS on the smallest card that fits. Setting a floor drops the cards that only manage Hermes 3 405B by squeezing it further than you would want.

  4. 04

    Compare tokens per second, not specifications

    Ranking by tokens per second for Hermes 3 405B follows memory bandwidth, not core counts, which is why the B300 tops it at 19.3 tok/s.

  5. 05

    Read the fit column last

    The fit column separates cards that just manage Hermes 3 405B from those with room to spare. Buy for the second if the context might grow.

  6. 06

    Check the card from the other side

    Following a card through to its own page shows every other model it can hold, which is the question that follows once Hermes 3 405B is settled.

Answers

Hermes 3 405B — common questions

01

Where can I download Hermes 3 405B?

Its weights are published under the NousResearch organisation on Hugging Face. We do not host model files — this site calculates what hardware is needed to run them.

02

Can I run Hermes 3 405B if it does not fit in my GPU?

It can be split between the card and system memory, but Hermes 3 405B generates painfully slowly that way — the nearest miss we calculate is short by 72.9 GB. Nothing on this page assumes offloading.

03

Would two GPUs run Hermes 3 405B faster?

Capacity adds across cards; throughput does not. Since 4 of the cards we track already hold Hermes 3 405B on their own, a second card is rarely the answer here.

04

Why does the quantisation differ between cards for Hermes 3 405B?

A larger card holds a more accurate copy. Across the cards that run Hermes 3 405B, 2 compression levels are used; the floor control above pins it to one.

05

How accurate are these Hermes 3 405B speed estimates?

They are calculated from specifications rather than measured, and each carries a range — 12–31 tok/s on the B300, for instance. The same model and card vary by thirty to fifty per cent depending on the inference software and its version.

06

What GPU do I need to run Hermes 3 405B?

The smallest card in our catalogue that holds Hermes 3 405B is the Radeon Instinct MI325X, with 256 GB of memory. It runs the model at IQ4_XS using about 222.1 GB, and produces roughly 12.0 tokens per second. 4 cards in total can run it.

07

How fast is Hermes 3 405B on a GPU?

It depends on the card. The quickest we calculate is a B300 at about 19.3 tokens per second; the slowest that still runs it manages considerably less. Reading speed is around ten tokens per second, and 4 of the cards that can run Hermes 3 405B clear that.

08

How much VRAM does Hermes 3 405B need?

About 222.1 GB at IQ4_XS compression, which is what the smallest card that runs it uses. Less compression needs more: the figures in the memory column above are recalculated for each card, because each one holds the least-compressed version it can.

09

Is Hermes 3 405B open source?

Its weights are published, so Hermes 3 405B can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.

10

How many parameters does Hermes 3 405B have?

Hermes 3 405B has 405B parameters. 405B. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.

11

Who created Hermes 3 405B?

Hermes 3 405B was published by Nous Research, based in United States of America, categorised as industry.

12

When was Hermes 3 405B released?

Hermes 3 405B was published in August 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.

13

What is Hermes 3 405B used for?

Hermes 3 405B works in Language, and is recorded as handling language modeling/generation, Chat, Question answering. These are the areas it was designed around; they describe intent rather than a hard boundary.

Source

Original publication

Record last updated 28 November 2025

The other direction

Looking at it from the other side?

This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.