What are the hardware requirements for MN GRAND Gutenberg Lyra4 Lyra 23B V2?

MN GRAND Gutenberg Lyra4 Lyra 23B V2 requires approximately 44.4 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MN GRAND Gutenberg Lyra4 Lyra 23B V2 and how large is it?

MN GRAND Gutenberg Lyra4 Lyra 23B V2 is developed by DavidAU, a model with 23b 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 MN GRAND Gutenberg Lyra4 Lyra 23B V2?

MN GRAND Gutenberg Lyra4 Lyra 23B V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MN GRAND Gutenberg Lyra4 Lyra 23B V2 by DavidAU — VRAM 44.4GB, 1000K context

Name: MN GRAND Gutenberg Lyra4 Lyra 23B V2
Author: DavidAU

MN GRAND Gutenberg Lyra4 Lyra 23B V2 is an open-source language model by DavidAU. Features: 23b LLM, VRAM: 44.4GB, Context: 1000K, LLM Explorer Score: 0.15.

Autotrain compatible Conversational Endpoints compatible Merge Mergekit Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-23B-V2

MN GRAND Gutenberg Lyra4 Lyra 23B V2 Parameters and Internals

LLM Name	MN GRAND Gutenberg Lyra4 Lyra 23B V2
Repository 🤗	https://huggingface.co/DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-23B-V2
Model Size	23b
Required VRAM	44.4 GB
Updated	2025-09-23
Maintainer	DavidAU
Model Type	mistral
Model Files	1.3 GB: 1-of-48 1.3 GB: 2-of-48 1.0 GB: 3-of-48 0.9 GB: 4-of-48 1.0 GB: 5-of-48 0.9 GB: 6-of-48 0.9 GB: 7-of-48 1.0 GB: 8-of-48 0.9 GB: 9-of-48 0.9 GB: 10-of-48 1.0 GB: 11-of-48 1.0 GB: 12-of-48 0.9 GB: 13-of-48 0.9 GB: 14-of-48 0.9 GB: 15-of-48 0.9 GB: 16-of-48 1.0 GB: 17-of-48 1.0 GB: 18-of-48 1.0 GB: 19-of-48 0.9 GB: 20-of-48 0.9 GB: 21-of-48 0.9 GB: 22-of-48 0.9 GB: 23-of-48 0.9 GB: 24-of-48 1.0 GB: 25-of-48 0.9 GB: 26-of-48 0.9 GB: 27-of-48 0.9 GB: 28-of-48 0.9 GB: 29-of-48 0.9 GB: 30-of-48 0.9 GB: 31-of-48 0.9 GB: 32-of-48 0.9 GB: 33-of-48 1.0 GB: 34-of-48 0.9 GB: 35-of-48 0.9 GB: 36-of-48 0.9 GB: 37-of-48 1.0 GB: 38-of-48 1.0 GB: 39-of-48 0.9 GB: 40-of-48 0.9 GB: 41-of-48 0.9 GB: 42-of-48 0.9 GB: 43-of-48 0.9 GB: 44-of-48 0.9 GB: 45-of-48 1.0 GB: 46-of-48 0.9 GB: 47-of-48
Model Architecture	MistralForCausalLM
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.43.3
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the MN GRAND Gutenberg Lyra4 Lyra 23B V2 capabilities

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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 MN GRAND Gutenberg Lyra4 Lyra 23B V2

Best Alternatives	Context / RAM	Downloads
...ppelKartoffel Mistral Nemo 23B	1000K / 46.3 GB	10
Mergekit Ties Asjuuws	1000K / 45.7 GB	6
Mergekit Model Stock Gcraeln	1000K / 45.7 GB	5

Note: green Score (e.g. "73.2") means that the model is better than DavidAU/MN-GRAND-Gutenberg-Lyra4-Lyra-23B-V2.