Models / Nous Research/ Hermes 4 405B

Hermes 4 405B

Nous Research · released Aug 6, 2025 · NousResearch/Hermes-4-405B

Input: text. Output: text.InputOutput
Type
Open weightsLlama 3 Community License
Params
406B
Context
131K

about 98K words of context · download allowed, licence restricts use

Our take

Written Aug 3, 2026

Hermes 4 is a 405.9-billion-parameter text model from Nous Research with a 131,072-token request limit. Its weights can be downloaded under a restricted community licence, and it is available from two hosts at matching rates with no price premium between them.

Who should pick it

Pick this for large-context text work that needs a 131,072-token window, or when you want a very large downloadable model at a predictable rate across both tracked providers. Use it if 34 tokens per second on Nebius meets your latency needs. Skip it if you need measured quality scores, a fully permissive licence for commercial use, or verified speed on OpenRouter.

The case for it

  • 405.9 billion parameters, placing it among the largest downloadable models.
  • Identical pricing across both providers, so there is no premium for choosing one over the other.
  • Throughput is measured at 34 tokens per second on Nebius.

The case against it

  • No benchmark scores in our data — chat, reasoning, coding and other quality metrics are all unverified.
  • Restricted licence: the Llama 3 Community Licence requires a separate Meta agreement for commercial use, unlike Apache 2.0 or fully permissive alternatives.
  • Speed on OpenRouter is undisclosed in our data.
00

How good is it?

We hold no score for this model.

We look for every model we track on every board we watch, and none of them has turned up Hermes 4 405B — so there is no intelligence, coding, agentic or writing score to show you, not a low one, none.

The boards we watch →

01

Can you run it yourself?

Fits in memory
weights load entirely on the card
Spills to system RAM
some weights offload; much slower
Too large
will not load even with offload
est
size is calculated; the verdict could change by 10%
A card many people ownToo large

GeForce RTX 4090 · 24 GB

Weights at Q4_K_M255.9 / 24 GBest
Usable contextNot calculated for spilled setups
Decode speedNot estimated for spilled setups

Too large for this card. The weights do not fit even with part of them offloaded to system memory.

One step upToo large

Apple M1 Pro (16-core GPU) · 32 GB

Weights at Q4_K_M255.9 / 32 GBest
Usable contextNot calculated for spilled setups
Decode speedNot estimated for spilled setups

Too large for this card. The weights do not fit even with part of them offloaded to system memory.

Comfortable fit

On a MacFits in memory

Apple M3 Ultra (80-core GPU) · 512 GB

Weights at Q4_K_M255.9 / 512 GBest
Spare memory118.1 GB spare
Usable context131K of 131K
Decode speed2 tok/sest

Room to spare. 118.1 GB spare means a 10% error in the size would not change the answer.

Your hardware
Checking your profile…

Memory use by level

Against a 24 GB card.

Q4_K_M
recommended
255.9 GBest
Too large
Q5_K_M
300.2 GBest
Too large
Q8_0
448.5 GBest
Too large

All 3 sizes here are calculated, not measured. We hold no measured file for this model, so each size comes from the parameter count and every verdict above inherits that uncertainty.

Check against your own machine → · All 71 devices, with every size →

02

Or rent it from someone else

Cheapest published offer

Cheapest of 2 live listings. Picked at the widest standard context we hold, within one quantisation slice, so the numbers beside it are a price one host actually charges.

per 1M tokens
$1.00 in / $3.00 out
Context served
131K
Throughput
Not measured
Current provider offers with price, context and prompt-privacy answers
ProviderIn / out per 1M tokensContextThroughputTrains on promptsLogs promptsZero retention
OpenRouter$1.00 / $3.00131Knot measuredUnknownUnknownUnknown
Nebius AI Studiofp8$1.00 / $3.00131K29 tok/sNoNoConfirmed

Across the 2 listings we hold: 1 say they do not train on prompts, 0 say they do and 1 do not say. 1 appear in the zero-retention registry we check; the rest are unknown to us rather than confirmed either way.

What each host's API supports

From the parameter list each endpoint publishes. Streaming is omitted: nothing we hold reports it, for any model.

Supported
Not supported
Not published
host gave no parameter list
API features per host
ProviderTool callingJSON outputStrict schema
OpenRouter
Nebius AI Studiofp8

Tool calling: 0 of 2 listings say yes, 2 say no. JSON output: 2 of 2 listings say yes. Strict schema: 0 of 2 listings say yes, 2 say no.

03

Models people weigh against Hermes 4 405B

04

When we formed this view

Dates behind this page

Jul 26, 2026ListedListed on LLMapfirst indexed by our pipeline
Aug 6, 2025AnnouncedHermes 4 405B announced by Nous Research

Prices last checked 3d ago

What we do not know about this model yet

  • We hold no measured file for it, so all 3 sizes on this page are calculated from the parameter count.
  • No board we watch has turned up a score, so we hold no quality figures at all.
  • Nothing we hold says whether an endpoint streams, so we do not show it either way.
  • 1 of 2 listings do not say whether they train on prompts.
  • We hold no cached-input rate for any of its listings.
05

Licence and identifiers

What the licence allowsLlama 3 Community License, what it allows commercially, and the identifiers you need to pull this model — its Hugging Face repo, our slug and a machine-readable card.

Licence

Llama 3 Community License

restricted_openCommercial use allowed

Commercial use allowed below 700M MAU; requires "Built with Meta Llama 3" attribution and Llama naming on derivatives.

Identifiers

Architecture
Dense
Modality record
text->text
Catalogue slug
nousresearch-hermes-4-405b

Machine-readable model card (omc.json) →

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