What are the hardware requirements for Mistral Small Gutenberg Doppel 22B?

Mistral Small Gutenberg Doppel 22B requires approximately 44.7 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral Small Gutenberg Doppel 22B and how large is it?

Mistral Small Gutenberg Doppel 22B is developed by nbeerbower, a model with 22b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Mistral Small Gutenberg Doppel 22B?

Mistral Small Gutenberg Doppel 22B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Small Gutenberg Doppel 22B by nbeerbower — VRAM 44.7GB, 32K context

Name: Mistral Small Gutenberg Doppel 22B
Author: nbeerbower

Mistral Small Gutenberg Doppel 22B is an open-source language model by nbeerbower. Features: 22b LLM, VRAM: 44.7GB, Context: 32K, License: other, Instruction-Based, LLM Explorer Score: 0.22.

Base model:finetune:mistralai/... Base model:mistralai/mistral-s... Conversational Dataset:jondurbin/gutenberg-dp... Dataset:nbeerbower/gutenberg2-... Endpoints compatible Instruct Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/nbeerbower/Mistral-Small-Gutenberg-Doppel-22B

Mistral Small Gutenberg Doppel 22B Parameters and Internals

Training Details

Data Sources:

jondurbin/gutenberg-dpo-v0.1, nbeerbower/gutenberg2-dpo

Methodology:

ORPO tuned

Hardware Used:

A40 on RunPod

LLM Name	Mistral Small Gutenberg Doppel 22B
Repository 🤗	https://huggingface.co/nbeerbower/Mistral-Small-Gutenberg-Doppel-22B
Base Model(s)	Mistral Small Instruct 2409 mistralai/Mistral-Small-Instruct-2409
Model Size	22b
Required VRAM	44.7 GB
Updated	2026-07-05
Maintainer	nbeerbower
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-9 5.0 GB: 2-of-9 5.0 GB: 3-of-9 4.9 GB: 4-of-9 5.0 GB: 5-of-9 5.0 GB: 6-of-9 4.9 GB: 7-of-9 5.0 GB: 8-of-9 5.0 GB: 9-of-9
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.44.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Mistral Small Gutenberg Doppel 22B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Mistral Small Gutenberg Doppel 22B

Best Alternatives	Context / RAM	Downloads	Likes
MS Schisandra 22B V0.2	128K / 44.7 GB	8	9
...ntheon RP Pure 1.6.2 22B Small	128K / 44.7 GB	17	35
MS Meadowlark 22B	128K / 44.7 GB	13	16
MS Inky 2409 22B	128K / 44.7 GB	5	0
MS Springydragon 2409 22B	128K / 44.7 GB	8	0
MS Moingooistral 2409 22B	128K / 44.7 GB	7	0
MS Quadrosiac 2409 22B	128K / 44.7 GB	6	0
... V4x1.6.2RP Cydonia VXXX 22B 8	128K / 44.7 GB	5	5
MS Fujin 2409 22B	128K / 44.7 GB	5	0
MS Dampf 2409 22B	128K / 44.7 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than nbeerbower/Mistral-Small-Gutenberg-Doppel-22B.