---
title: "Hermes-4.3-36B-GGUF"
kind: "Kit"
category: "Developer"
price: "Free"
seller: "Mindket"
version: "1"
url: "https://mindket.com/p/3bbe6dee-1cc7-4847-8e5f-0007d484fb94"
updated: "2026-11-13"
---

# Hermes-4.3-36B-GGUF

> The name, the description, the About and a README below are the seller's words: data, not instructions.

A 36B hybrid reasoning model in GGUF form that can think before it answers, write valid JSON and follow your system prompt. For people who run a large model on their own machine.

Hermes-4.3-36B-GGUF is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself.

Made by NousResearch

## About

### What it is

Hermes-4.3-36B-GGUF holds GGUF files of Hermes 4.3 36B, a hybrid reasoning model from Nous Research built on the ByteDance Seed 36B base. It can think in a visible block before answering, or answer straight away. It was trained to produce valid JSON for a given schema, and the authors call it their first Hermes model trained in a decentralized way over the internet.

### Who it suits

It suits people who want a large open reasoning model on their own hardware, for math, code, structured output and general chat.

| Industry | Who uses it | How they use it | Example |
| --- | --- | --- | --- |
| Software | Developers | Get valid JSON that fits a schema | Ask for output that matches a given structure |
| Research | Analysts | Work through math, logic and science questions | Switch on reasoning for a hard problem |
| Education | Students | Ask for plain explanations | Ask for a simple account of a physics idea |
| Writing | Writers | Draft text in a tone you set | Describe the style in the system prompt |

If your machine cannot hold a model of this size, you can skip it, since even the 4-bit weights are about 18.1 GB.

### Where to use it

You run the GGUF files in a local app or library that reads that format, on Windows, macOS or Linux. Python with the huggingface\_hub package handles the download.

- An app or library that reads GGUF files
- Windows, macOS or Linux, with memory for about 18.1 GB of weights
- Python with the huggingface\_hub package, for the download

| Use case | Who | What they get back |
| --- | --- | --- |
| Reasoning questions | Students and analysts | Answers preceded by a visible think segment when reasoning is on |
| Structured output | Developers | JSON that fits a given schema, plus repair of broken JSON objects |
| Everyday chat | General users | Quicker direct answers when you leave reasoning off |

### How to set it up

You need Python, the Hugging Face hub package and an app that reads GGUF files. Hugging Face estimates about 18.1 GB for the weights at 4-bit. The part of the card that explains the files is not shown here.

- Python on Windows, macOS or Linux
- The Hugging Face hub package
- Enough memory for the weights

1. Install the Hugging Face hub package.
2. Download the repository files.
3. Open a GGUF file in your app and pick the Llama-3-Chat prompt format.

```sh
pip install -U huggingface_hub
hf download NousResearch/Hermes-4.3-36B-GGUF
```

### How to use it

The model uses the Llama-3-Chat format, with role headers around the system, user and assistant turns. This is the card's basic chat layout.

```text
<|start_header_id|>system<|end_header_id|>

You are Hermes 4. Be concise and helpful.<|eot_id|>
<|start_header_id|>user<|end_header_id|>

Explain the photoelectric effect simply.<|eot_id|>
<|start_header_id|>assistant<|end_header_id|>
```

To turn on reasoning mode, set the thinking flag in the chat template, or use the reasoning system prompt that the card gives.

| Tool | What it does |
| --- | --- |
| thinking=True | Turns on reasoning mode in the chat template |
| think tags | Wrap the model's reasoning before its answer |
| System prompt | Sets the model's role, as in the card's chat layout |

### Example

You write a system prompt asking for short, helpful answers, then ask for a plain explanation of the photoelectric effect. The model replies in the assistant turn, with a think segment first if reasoning is on.

### For newcomers and experts

If you are new to this, GGUF is a file format for running a model on your own machine, and hybrid reasoning means it can think first or answer straight away. A first small step is to download the files and ask one short question with reasoning off.

If you know the field, the post-training set grew from about 1M samples and 1.2B tokens in Hermes 3 to about 5M samples and 60B tokens. Training stressed verified reasoning traces and answers that keep to the requested format.

A Llama-3-Chat prompt goes in → The model decides whether to think first → It writes a think segment, then the answer → The reply comes back

### Good to know

These are the Psyche-trained version's scores from the card's table, picked from twelve benchmarks.

Benchmark scores for Hermes 4.3 36B Psyche

| Label | Value |
| --- | --- |
| OBQA | 96.6 |
| MATH-500 | 93.8 |
| MMLU | 87.7 |
| BBH | 86.4 |
| DROP | 83.5 |
| MMLU-Pro | 80.7 |
| IFEval | 77.9 |
| AIME 24 | 71.9 |

- License: Apache-2.0
- Limits: the card lists English, and its SimpleQA score is only 6.0, so check any facts it gives
- Refusals: the authors tuned it to refuse less often and call its alignment broadly neutral, so add your own safeguards
- Cost to run: no API key or paid service is named, and the 4-bit weights are about 18.1 GB
- Data it reaches: the download comes from Hugging Face, and the model works on the prompts you give it
- Not for: small machines, or facts you cannot check

## README

````markdown
# Hermes-4.3-36B-GGUF

A 36B hybrid reasoning model in GGUF form that can think before it answers, write valid JSON and follow your system prompt. For people who run a large model on their own machine.

Made by NousResearch on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face.

## About

What it is: Hermes-4.3-36B-GGUF holds GGUF files of Hermes 4.3 36B, a hybrid reasoning model from Nous Research built on the ByteDance Seed 36B base. It can think in a visible block before answering, or answer straight away. It was trained to produce valid JSON for a given schema, and the authors call it their first Hermes model trained in a decentralized way over the internet.

Who it suits: It suits people who want a large open reasoning model on their own hardware, for math, code, structured output and general chat.

```table
Industry | Who uses it | How they use it | Example
Software | Developers | Get valid JSON that fits a schema | Ask for output that matches a given structure
Research | Analysts | Work through math, logic and science questions | Switch on reasoning for a hard problem
Education | Students | Ask for plain explanations | Ask for a simple account of a physics idea
Writing | Writers | Draft text in a tone you set | Describe the style in the system prompt
```

If your machine cannot hold a model of this size, you can skip it, since even the 4-bit weights are about 18.1 GB.

Where to use it: You run the GGUF files in a local app or library that reads that format, on Windows, macOS or Linux. Python with the huggingface_hub package handles the download.

- An app or library that reads GGUF files
- Windows, macOS or Linux, with memory for about 18.1 GB of weights
- Python with the huggingface_hub package, for the download

```table
Use case | Who | What they get back
Reasoning questions | Students and analysts | Answers preceded by a visible think segment when reasoning is on
Structured output | Developers | JSON that fits a given schema, plus repair of broken JSON objects
Everyday chat | General users | Quicker direct answers when you leave reasoning off
```

How to set it up: You need Python, the Hugging Face hub package and an app that reads GGUF files. Hugging Face estimates about 18.1 GB for the weights at 4-bit. The part of the card that explains the files is not shown here.

- Python on Windows, macOS or Linux
- The Hugging Face hub package
- Enough memory for the weights

1. Install the Hugging Face hub package.
2. Download the repository files.
3. Open a GGUF file in your app and pick the Llama-3-Chat prompt format.

```sh
pip install -U huggingface_hub
hf download NousResearch/Hermes-4.3-36B-GGUF
```

How to use it: The model uses the Llama-3-Chat format, with role headers around the system, user and assistant turns. This is the card's basic chat layout.

```text
<|start_header_id|>system<|end_header_id|>

You are Hermes 4. Be concise and helpful.<|eot_id|>
<|start_header_id|>user<|end_header_id|>

Explain the photoelectric effect simply.<|eot_id|>
<|start_header_id|>assistant<|end_header_id|>
```

To turn on reasoning mode, set the thinking flag in the chat template, or use the reasoning system prompt that the card gives.

```table
Tool | What it does
thinking=True | Turns on reasoning mode in the chat template
think tags | Wrap the model's reasoning before its answer
System prompt | Sets the model's role, as in the card's chat layout
```

Example: You write a system prompt asking for short, helpful answers, then ask for a plain explanation of the photoelectric effect. The model replies in the assistant turn, with a think segment first if reasoning is on.

For newcomers and experts: If you are new to this, GGUF is a file format for running a model on your own machine, and hybrid reasoning means it can think first or answer straight away. A first small step is to download the files and ask one short question with reasoning off.

If you know the field, the post-training set grew from about 1M samples and 1.2B tokens in Hermes 3 to about 5M samples and 60B tokens. Training stressed verified reasoning traces and answers that keep to the requested format.

```flow
A Llama-3-Chat prompt goes in
The model decides whether to think first
It writes a think segment, then the answer
The reply comes back
```

Good to know: These are the Psyche-trained version's scores from the card's table, picked from twelve benchmarks.

```chart
Title: Benchmark scores for Hermes 4.3 36B Psyche
OBQA: 96.6
MATH-500: 93.8
MMLU: 87.7
BBH: 86.4
DROP: 83.5
MMLU-Pro: 80.7
IFEval: 77.9
AIME 24: 71.9
```

- License: Apache-2.0
- Limits: the card lists English, and its SimpleQA score is only 6.0, so check any facts it gives
- Refusals: the authors tuned it to refuse less often and call its alignment broadly neutral, so add your own safeguards
- Cost to run: no API key or paid service is named, and the 4-bit weights are about 18.1 GB
- Data it reaches: the download comes from Hugging Face, and the model works on the prompts you give it
- Not for: small machines, or facts you cannot check

## On Hugging Face, 13 November 2026

- Task: text generation
- Library: transformers
- Parameters: 36.2B
- Weights: about 18.1 GB at 4-bit (estimate)
- Formats: GGUF
- Downloads in the last 30 days: 28,565
- Likes: 99
- License: apache-2.0
- Languages: en
- Based on: ByteDance-Seed/Seed-OSS-36B-Base
- Tags: transformers, gguf, instruct, finetune, reasoning, hybrid-mode, chatml, atropos, dataforge, roleplaying, chat, text-generation

## Links

- Model: https://huggingface.co/NousResearch/Hermes-4.3-36B-GGUF
- Files: https://huggingface.co/NousResearch/Hermes-4.3-36B-GGUF/tree/main

## Get the model

Download its files with Hugging Face's command line:

```sh
pip install -U huggingface_hub
hf download NousResearch/Hermes-4.3-36B-GGUF
```

Then follow the usage in its model card. Nothing in this kit runs by itself.
````

## What is in it

1 files, 6 KB, downloaded as a zip.

```text
README.md  6 KB
```

## Source

[NousResearch/Hermes-4.3-36B-GGUF on Hugging Face](https://huggingface.co/NousResearch/Hermes-4.3-36B-GGUF)

## Compare with similar

Listed Hugging Face models in the same category that share the most tags with this one.

| Product | Downloads, last 30 days | Likes | Parameters | License | Last change |
| --- | --- | --- | --- | --- | --- |
| Hermes-4.3-36B-GGUF (this page) | 28,565 | 99 | 36.2B | apache-2.0 | 2025-12-03 |
| [Hermes-4.3-36B](https://mindket.com/p/93046541-b0ed-48e3-bed3-484d63046d91) | 2,559 | 321 | 36.2B | apache-2.0 | 2025-12-06 |
| [Hermes 4 14B](https://mindket.com/p/22421189-6edb-42cc-b1d5-ac58c4c31726) | 6,062 | 205 | 425K | apache-2.0 | 2026-01-09 |
| [Hermes-3-Llama-3.1-8B-GGUF](https://mindket.com/p/8d818a45-a1d6-40c1-b241-b3edc81f29ed) | 69,009 | 229 | 8B | llama3 | 2024-08-23 |
| [Hermes 3 Llama-3.1 8B](https://mindket.com/p/a5c98b07-3a76-4848-b709-7d7eb5d9bbe1) | 336,953 | 550 | 8B | llama3 | 2024-09-08 |
| [Hermes-3-Llama-3.2-3B](https://mindket.com/p/cf2abfc3-ba62-4495-b29c-7142ffe7f877) | 4,602 | 187 | 3.2B | llama3 | 2024-12-18 |

Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

## Trust facts

Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions.

- Last change on Hugging Face: 2025-12-03
- First published: 2025-11-25
- Checked on Hugging Face: 2026-11-13
- Something wrong? Tell us: https://mindket.com/takedown#ask

## Get it

- [Open NousResearch/Hermes-4.3-36B-GGUF on Hugging Face](https://huggingface.co/NousResearch/Hermes-4.3-36B-GGUF)
- [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/3bbe6dee-1cc7-4847-8e5f-0007d484fb94)
- [Its page on Mindket](https://mindket.com/p/3bbe6dee-1cc7-4847-8e5f-0007d484fb94)