What are the hardware requirements for Qwen2.5 14B Wernicke SFT?

Qwen2.5 14B Wernicke SFT requires approximately 29.6 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 Qwen2.5 14B Wernicke SFT and how large is it?

Qwen2.5 14B Wernicke SFT is developed by CultriX, 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 Qwen2.5 14B Wernicke SFT?

Qwen2.5 14B Wernicke SFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 14B Wernicke SFT by CultriX — VRAM 29.6GB, 128K context

Name: Qwen2.5 14B Wernicke SFT
Author: CultriX

Qwen2.5 14B Wernicke SFT is an open-source language model by CultriX. Features: 14b LLM, VRAM: 29.6GB, Context: 128K, License: apache-2.0, LLM Explorer Score: 0.25.

Arxiv:2403.19522 Base model:cultrix/qwen2.5-14b... Base model:finetune:cultrix/qw... Conversational Dataset:ajibawa-2023/python-co... Dataset:cultrix/uptodate-small Dataset:isaiahbjork/chain-of-t... Dataset:shibing624/sharegpt gp... Dataset:theblackcat102/sharegp... En Gpt4 Medical Merge Mergekit Model-index Qwen2 Region:us Safetensors Sft Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/CultriX/Qwen2.5-14B-Wernicke-SFT

Qwen2.5 14B Wernicke SFT Parameters and Internals

LLM Name	Qwen2.5 14B Wernicke SFT
Repository 🤗	https://huggingface.co/CultriX/Qwen2.5-14B-Wernicke-SFT
Base Model(s)	CultriX/Qwen2.5-14B-Wernicke CultriX/Qwen2.5-14B-Wernicke
Model Size	14b
Required VRAM	29.6 GB
Updated	2026-08-25
Maintainer	CultriX
Model Type	qwen2
Model Files	3.9 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 1.7 GB: 8-of-8
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 14B Wernicke SFT 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 Qwen2.5 14B Wernicke SFT

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 CultriX/Qwen2.5-14B-Wernicke-SFT.