What are the hardware requirements for Amaterasu 123B?

Amaterasu 123B requires approximately 212.4 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 Amaterasu 123B and how large is it?

Amaterasu 123B is developed by Aratako, 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 Amaterasu 123B?

Amaterasu 123B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Amaterasu 123B by Aratako — VRAM 212.4GB, 128K context

Name: Amaterasu 123B
Author: Aratako

Amaterasu 123B is an open-source language model by Aratako. Features: 123b LLM, VRAM: 212.4GB, Context: 128K, License: other, Instruction-Based, LLM Explorer Score: 0.19.

Base model:finetune:mistralai/... Base model:mistralai/mistral-l... Conversational Endpoints compatible Instruct Ja Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Aratako/Amaterasu-123B

Amaterasu 123B Parameters and Internals

LLM Name	Amaterasu 123B
Repository 🤗	https://huggingface.co/Aratako/Amaterasu-123B
Base Model(s)	Mistral Large Instruct 2411 mistralai/Mistral-Large-Instruct-2411
Model Size	123b
Required VRAM	212.4 GB
Updated	2026-10-12
Maintainer	Aratako
Model Type	mistral
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-51 4.8 GB: 2-of-51 4.9 GB: 3-of-51 4.8 GB: 4-of-51 4.8 GB: 5-of-51 4.8 GB: 6-of-51 4.9 GB: 7-of-51 4.8 GB: 8-of-51 4.8 GB: 9-of-51 4.8 GB: 10-of-51 4.9 GB: 11-of-51 4.8 GB: 12-of-51 4.8 GB: 13-of-51 4.8 GB: 14-of-51 4.9 GB: 15-of-51 4.8 GB: 16-of-51 4.8 GB: 17-of-51 4.8 GB: 18-of-51 4.9 GB: 19-of-51 4.8 GB: 20-of-51 4.8 GB: 21-of-51 4.8 GB: 22-of-51 4.9 GB: 23-of-51 4.8 GB: 24-of-51 4.8 GB: 25-of-51 4.8 GB: 26-of-51 4.9 GB: 27-of-51 4.8 GB: 28-of-51 4.8 GB: 29-of-51 4.8 GB: 30-of-51 4.9 GB: 31-of-51 4.8 GB: 32-of-51 4.8 GB: 33-of-51 4.8 GB: 34-of-51 4.9 GB: 35-of-51 4.8 GB: 36-of-51 4.8 GB: 37-of-51 4.8 GB: 38-of-51 4.9 GB: 39-of-51 4.8 GB: 40-of-51 4.8 GB: 41-of-51 4.8 GB: 42-of-51 4.9 GB: 43-of-51 4.8 GB: 44-of-51
Supported Languages	ja
Model Architecture	MistralForCausalLM
License	other
Context Length	131072
Model Max Length	131072
Transformers Version	4.52.3
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Amaterasu 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 Amaterasu 123B

Best Alternatives	Context / RAM	Downloads	Likes
Behemoth ReduX 123B V1.1	128K / 226.4 GB	37	5
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	91	13
Gigaberg Mistral Large 123B	128K / 222 GB	6	2
Cakrawala 123B	128K / 222 GB	6	4
Behemoth 123B V2	128K / 221.6 GB	4	10
Behemoth 123B V1	128K / 221.6 GB	6	44
Magnum V4 123B	128K / 222 GB	22	33

Note: green Score (e.g. "73.2") means that the model is better than Aratako/Amaterasu-123B.