What are the hardware requirements for ZYH LLM Qwen2.5 14B V3?

ZYH LLM Qwen2.5 14B V3 requires approximately 29.7 GB of VRAM and supports a context window of 986K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ZYH LLM Qwen2.5 14B V3 and how large is it?

ZYH LLM Qwen2.5 14B V3 is developed by YOYO-AI, 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 ZYH LLM Qwen2.5 14B V3?

ZYH LLM Qwen2.5 14B V3 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ZYH LLM Qwen2.5 14B V3 by YOYO-AI — VRAM 29.7GB, 986K context

Name: ZYH LLM Qwen2.5 14B V3
Author: YOYO-AI

ZYH LLM Qwen2.5 14B V3 is an open-source language model by YOYO-AI. Features: 14b LLM, VRAM: 29.7GB, Context: 986K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.29.

Base model:arcee-ai/virtuoso-s... Base model:azure99/blossom-v6-... Base model:merge:arcee-ai/virt... Base model:merge:azure99/bloss... Base model:merge:qwen/qwen2.5-... Base model:merge:qwen/qwen2.5-... Base model:merge:qwen/qwen2.5-... Base model:qwen/qwen2.5-14b Base model:qwen/qwen2.5-14b-in... Base model:qwen/qwen2.5-14b-in... Conversational En Instruct Merge Model-index Qwen2 Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/YOYO-AI/ZYH-LLM-Qwen2.5-14B-V3

ZYH LLM Qwen2.5 14B V3 Parameters and Internals

LLM Name	ZYH LLM Qwen2.5 14B V3
Repository 🤗	https://huggingface.co/YOYO-AI/ZYH-LLM-Qwen2.5-14B-V3
Base Model(s)	Qwen/Qwen2.5-14B Blossom V6 14B Virtuoso Small V2 Qwen/Qwen2.5-14B-Instruct Qwen/Qwen2.5-14B-Instruct-1M Qwen/Qwen2.5-14B Azure99/Blossom-V6-14B arcee-ai/Virtuoso-Small-v2 Qwen/Qwen2.5-14B-Instruct Qwen/Qwen2.5-14B-Instruct-1M
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-06-28
Maintainer	YOYO-AI
Model Type	qwen2
Instruction-Based	Yes
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 zh
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	1010000
Model Max Length	1010000
Transformers Version	4.48.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the ZYH LLM Qwen2.5 14B V3 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 ZYH LLM Qwen2.5 14B V3

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
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Impish QWEN 14B 1M	986K / 29.7 GB	56	26
Q2.5 14B Instruct 1M Harmony	986K / 29.7 GB	3	1
Calcium Opus 14B Elite 1M	986K / 29.7 GB	15	4

Note: green Score (e.g. "73.2") means that the model is better than YOYO-AI/ZYH-LLM-Qwen2.5-14B-V3.