What are the hardware requirements for SauerkrautLM V2 14B DPO?

SauerkrautLM V2 14B DPO requires approximately 29.6 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SauerkrautLM V2 14B DPO and how large is it?

SauerkrautLM V2 14B DPO is developed by VAGOsolutions, a model with 14b 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 SauerkrautLM V2 14B DPO?

SauerkrautLM V2 14B DPO is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SauerkrautLM V2 14B DPO by VAGOsolutions — VRAM 29.6GB, 32K context

Name: SauerkrautLM V2 14B DPO
Author: VAGOsolutions

SauerkrautLM V2 14B DPO is an open-source language model by VAGOsolutions. Features: 14b LLM, VRAM: 29.6GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.25.

Ar Base model:finetune:vagosoluti... Base model:vagosolutions/sauer... Dataset:vagosolutions/sauerkra... Dataset:vagosolutions/sauerkra... De Dpo En Es Fr It Model-index Nl Pt Qwen2 Region:us Safetensors Sft Sharded Spectrum Tensorflow

Model Card on HF 🤗: https://huggingface.co/VAGOsolutions/SauerkrautLM-v2-14b-DPO

SauerkrautLM V2 14B DPO Parameters and Internals

LLM Name	SauerkrautLM V2 14B DPO
Repository 🤗	https://huggingface.co/VAGOsolutions/SauerkrautLM-v2-14b-DPO
Base Model(s)	SauerkrautLM V2 14B SFT VAGOsolutions/SauerkrautLM-v2-14b-SFT
Model Size	14b
Required VRAM	29.6 GB
Updated	2026-08-07
Maintainer	VAGOsolutions
Model Type	qwen2
Model Files	4.0 GB: 1-of-8 4.0 GB: 2-of-8 4.0 GB: 3-of-8 4.0 GB: 4-of-8 4.0 GB: 5-of-8 4.0 GB: 6-of-8 4.0 GB: 7-of-8 1.6 GB: 8-of-8
Supported Languages	de en it fr pt nl ar es
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.47.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the SauerkrautLM V2 14B DPO 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 SauerkrautLM V2 14B DPO

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Etr1o V1.2	986K / 29.7 GB	11	0
Impish QWEN 14B 1M	986K / 29.7 GB	56	26

Note: green Score (e.g. "73.2") means that the model is better than VAGOsolutions/SauerkrautLM-v2-14b-DPO.