What are the hardware requirements for Behemoth R1 123B V2?

Behemoth R1 123B V2 requires approximately 226.4 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 Behemoth R1 123B V2 and how large is it?

Behemoth R1 123B V2 is developed by TheDrummer, 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 R1 123B V2?

Behemoth R1 123B V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Behemoth R1 123B V2 by TheDrummer — VRAM 226.4GB, 128K context

Name: Behemoth R1 123B V2
Author: TheDrummer

Behemoth R1 123B V2 is an open-source language model by TheDrummer. Features: 123b LLM, VRAM: 226.4GB, Context: 128K, Instruction-Based, LLM Explorer Score: 0.2.

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

Model Card on HF 🤗: https://huggingface.co/TheDrummer/Behemoth-R1-123B-v2

Behemoth R1 123B V2 Parameters and Internals

LLM Name	Behemoth R1 123B V2
Repository 🤗	https://huggingface.co/TheDrummer/Behemoth-R1-123B-v2
Base Model(s)	Mistral Large Instruct 2411 mistralai/Mistral-Large-Instruct-2411
Model Size	123b
Required VRAM	226.4 GB
Updated	2026-07-27
Maintainer	TheDrummer
Model Type	mistral
Instruction-Based	Yes
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 4.9 GB: 46-of-51 4.8 GB: 47-of-51
Model Architecture	MistralForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.55.2
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Behemoth R1 123B V2 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 Behemoth R1 123B V2

Best Alternatives	Context / RAM	Downloads	Likes
Behemoth ReduX 123B V1	128K / 217.2 GB	70	14
Behemoth X 123B V2	128K / 217.2 GB	47	32
ML2 123B Magnum Diamond	128K / 212.4 GB	126	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
Magnum V2 123B	128K / 207.6 GB	62	64
Lumikabra 123B V0.4	128K / 216.7 GB	9	12

Note: green Score (e.g. "73.2") means that the model is better than TheDrummer/Behemoth-R1-123B-v2.