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

Qwen2.5 14B Vimarckoso requires approximately 29.7 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 Vimarckoso and how large is it?

Qwen2.5 14B Vimarckoso is developed by sometimesanotion, 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 Vimarckoso?

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

Qwen2.5 14B Vimarckoso by sometimesanotion — VRAM 29.7GB, 128K context

Name: Qwen2.5 14B Vimarckoso
Author: sometimesanotion

Qwen2.5 14B Vimarckoso is an open-source language model by sometimesanotion. Features: 14b LLM, VRAM: 29.7GB, Context: 128K, License: apache-2.0, Merged, LLM Explorer Score: 0.26.

Merged Model Arxiv:2403.19522 Autotrain compatible Base model:arcee-ai/virtuoso-s... Base model:cultrix/seqwence-14... Base model:eva-unit-01/eva-qwe... Base model:qwen/qwen2.5-14b Base model:vagosolutions/sauer... Conversational En Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso

Qwen2.5 14B Vimarckoso Parameters and Internals

LLM Name	Qwen2.5 14B Vimarckoso
Repository 🤗	https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso
Base Model(s)	SeQwence 14B EvolMerge Qwen/Qwen2.5-14B sometimesanotion/Lamarck-14B-v0.1-prose-model_stock EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2 SauerkrautLM V2 14B DPO Virtuoso Small sometimesanotion/lamarck-14b-v0.1-prose-model_stock CultriX/SeQwence-14B-EvolMerge Qwen/Qwen2.5-14B sometimesanotion/Lamarck-14B-v0.1-prose-model_stock EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2 VAGOsolutions/SauerkrautLM-v2-14b-DPO arcee-ai/Virtuoso-Small sometimesanotion/lamarck-14b-v0.1-prose-model_stock
Merged Model	Yes
Model Size	14b
Required VRAM	29.7 GB
Updated	2025-01-06
Maintainer	sometimesanotion
Model Type	qwen2
Model Files	4.9 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.8 GB: 6-of-6
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 14B Vimarckoso 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 Qwen2.5 14B Vimarckoso

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 sometimesanotion/Qwen2.5-14B-Vimarckoso.