What are the hardware requirements for Behemoth V1.2 Magnum V4 123B?

Behemoth V1.2 Magnum V4 123B requires approximately 216.7 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Behemoth V1.2 Magnum V4 123B and how large is it?

Behemoth V1.2 Magnum V4 123B is developed by knifeayumu, a model with 123b 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 Behemoth V1.2 Magnum V4 123B?

Behemoth V1.2 Magnum V4 123B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Behemoth V1.2 Magnum V4 123B by knifeayumu — VRAM 216.7GB, 128K context

Name: Behemoth V1.2 Magnum V4 123B
Author: knifeayumu

Behemoth V1.2 Magnum V4 123B is an open-source language model by knifeayumu. Features: 123b LLM, VRAM: 216.7GB, Context: 128K, License: other, Merged, LLM Explorer Score: 0.15.

Merged Model Base model:anthracite-org/magn... Base model:thedrummer/behemoth... Conversational Deploy:azure Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/knifeayumu/Behemoth-v1.2-Magnum-v4-123B

Behemoth V1.2 Magnum V4 123B Parameters and Internals

LLM Name	Behemoth V1.2 Magnum V4 123B
Repository 🤗	https://huggingface.co/knifeayumu/Behemoth-v1.2-Magnum-v4-123B
Base Model(s)	TheDrummer/Behemoth-123B-v1.2 Magnum V4 123B TheDrummer/Behemoth-123B-v1.2 anthracite-org/magnum-v4-123b
Merged Model	Yes
Model Size	123b
Required VRAM	216.7 GB
Updated	2026-07-10
Maintainer	knifeayumu
Model Type	mistral
Model Files	4.4 GB: 1-of-51 4.9 GB: 2-of-51 4.8 GB: 3-of-51 4.8 GB: 4-of-51 4.8 GB: 5-of-51 4.9 GB: 6-of-51 4.8 GB: 7-of-51 4.8 GB: 8-of-51 4.8 GB: 9-of-51 4.9 GB: 10-of-51 4.8 GB: 11-of-51 4.8 GB: 12-of-51 4.8 GB: 13-of-51 4.9 GB: 14-of-51 4.8 GB: 15-of-51 4.8 GB: 16-of-51 4.8 GB: 17-of-51 4.9 GB: 18-of-51 4.8 GB: 19-of-51 4.8 GB: 20-of-51 4.8 GB: 21-of-51 4.9 GB: 22-of-51 4.8 GB: 23-of-51 4.8 GB: 24-of-51 4.8 GB: 25-of-51 4.9 GB: 26-of-51 4.8 GB: 27-of-51 4.8 GB: 28-of-51 4.8 GB: 29-of-51 4.9 GB: 30-of-51 4.8 GB: 31-of-51 4.8 GB: 32-of-51 4.8 GB: 33-of-51 4.9 GB: 34-of-51 4.8 GB: 35-of-51 4.8 GB: 36-of-51 4.8 GB: 37-of-51 4.9 GB: 38-of-51 4.8 GB: 39-of-51 4.8 GB: 40-of-51 4.8 GB: 41-of-51 4.9 GB: 42-of-51 4.8 GB: 43-of-51 4.8 GB: 44-of-51 4.8 GB: 45-of-51
Model Architecture	MistralForCausalLM
License	other
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.2
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Behemoth V1.2 Magnum V4 123B 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 Behemoth V1.2 Magnum V4 123B

Best Alternatives	Context / RAM	Downloads	Likes
Behemoth X R1 123B	128K / 216.7 GB	8	2
Behemoth X 123B V2.1	128K / 222 GB	15	7
Behemoth ReduX 123B V1	128K / 217.2 GB	70	14
Behemoth X 123B V2	128K / 217.2 GB	47	32
Behemoth R1 123B V2	128K / 226.4 GB	12	29
ML2 123B Magnum Diamond	128K / 212.4 GB	126	13
Gigaberg Mistral Large 123B	128K / 222 GB	6	2
Monstral 123B V2	128K / 245.4 GB	107	48
Behemoth 123B V1.2	128K / 226.4 GB	6	30
Behemoth 123B V2.2	128K / 226.4 GB	7	27

Note: green Score (e.g. "73.2") means that the model is better than knifeayumu/Behemoth-v1.2-Magnum-v4-123B.