What are the hardware requirements for 70B Fallen SOGmv2?

70B Fallen SOGmv2 requires approximately 141.9 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 70B Fallen SOGmv2 and how large is it?

70B Fallen SOGmv2 is developed by schonsense, a model with 70b 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 70B Fallen SOGmv2?

70B Fallen SOGmv2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

70B Fallen SOGmv2 by schonsense — VRAM 141.9GB, 128K context

Name: 70B Fallen SOGmv2
Author: schonsense

70B Fallen SOGmv2 is an open-source language model by schonsense. Features: 70b LLM, VRAM: 141.9GB, Context: 128K, LLM Explorer Score: 0.19.

Autotrain compatible Base model:finetune:thedrummer... Base model:thedrummer/fallen-l... Conversational Endpoints compatible Llama Merge Mergekit Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/schonsense/70B_Fallen_SOGmv2

70B Fallen SOGmv2 Parameters and Internals

LLM Name	70B Fallen SOGmv2
Repository 🤗	https://huggingface.co/schonsense/70B_Fallen_SOGmv2
Base Model(s)	70B SOG MMv2 Ft TheDrummer/Fallen-Llama-3.3-70B-v1 schonsense/70B_SOG_MMv2_ft TheDrummer/Fallen-Llama-3.3-70B-v1
Model Size	70b
Required VRAM	141.9 GB
Updated	2025-09-12
Maintainer	schonsense
Model Type	llama
Model Files	4.7 GB: 1-of-30 4.7 GB: 2-of-30 5.0 GB: 3-of-30 5.0 GB: 4-of-30 4.7 GB: 5-of-30 4.7 GB: 6-of-30 4.7 GB: 7-of-30 5.0 GB: 8-of-30 5.0 GB: 9-of-30 4.7 GB: 10-of-30 4.7 GB: 11-of-30 4.7 GB: 12-of-30 5.0 GB: 13-of-30 5.0 GB: 14-of-30 4.7 GB: 15-of-30 4.7 GB: 16-of-30 4.7 GB: 17-of-30 5.0 GB: 18-of-30 5.0 GB: 19-of-30 4.7 GB: 20-of-30 4.7 GB: 21-of-30 4.7 GB: 22-of-30 5.0 GB: 23-of-30 5.0 GB: 24-of-30 4.7 GB: 25-of-30 4.7 GB: 26-of-30 4.7 GB: 27-of-30 5.0 GB: 28-of-30 5.0 GB: 29-of-30 2.0 GB: 30-of-30
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.50.3
Tokenizer Class	PreTrainedTokenizer
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the 70B Fallen SOGmv2 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

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