What are the hardware requirements for Qwen2.5 7B YOYO Super?

Qwen2.5 7B YOYO Super requires approximately 15.2 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 7B YOYO Super and how large is it?

Qwen2.5 7B YOYO Super is developed by YOYO-AI, a model with 7b 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 7B YOYO Super?

Qwen2.5 7B YOYO Super is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 7B YOYO Super by YOYO-AI — VRAM 15.2GB, 128K context

Name: Qwen2.5 7B YOYO Super
Author: YOYO-AI

Qwen2.5 7B YOYO Super is an open-source language model by YOYO-AI. Features: 7b LLM, VRAM: 15.2GB, Context: 128K, License: apache-2.0, Instruction-Based, Merged, LLM Explorer Score: 0.17.

Merged Model Base model:qwen/qwen2.5-7b Base model:qwen/qwen2.5-7b-ins... Base model:qwen/qwen2.5-7b-ins... Conversational En Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/YOYO-AI/Qwen2.5-7B-YOYO-super

Qwen2.5 7B YOYO Super Parameters and Internals

LLM Name	Qwen2.5 7B YOYO Super
Repository 🤗	https://huggingface.co/YOYO-AI/Qwen2.5-7B-YOYO-super
Base Model(s)	mergekit-community/Qwen2.5-7B-della mergekit-community/Qwen2.5-7B-ties Qwen/Qwen2.5-7B-Instruct Qwen/Qwen2.5-7B-Instruct-1M mergekit-community/Qwen2.5-7B-ties-1M Qwen/Qwen2.5-7B mergekit-community/Qwen2.5-7B-della-1M mergekit-community/Qwen2.5-7B-della mergekit-community/Qwen2.5-7B-ties Qwen/Qwen2.5-7B-Instruct Qwen/Qwen2.5-7B-Instruct-1M mergekit-community/Qwen2.5-7B-ties-1M Qwen/Qwen2.5-7B mergekit-community/Qwen2.5-7B-della-1M
Merged Model	Yes
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-07-10
Maintainer	YOYO-AI
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-4 4.9 GB: 2-of-4 5.0 GB: 3-of-4 0.3 GB: 4-of-4
Supported Languages	en zh
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 7B YOYO Super 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 7B YOYO Super

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen2.5 7B RRP 1M	986K / 15.2 GB	5	6
Qwen2.5 7B CelestialHarmony 1M	986K / 14.8 GB	8	7
Q2.5 Instruct 1M Harmony	986K / 15.2 GB	4	2
Impish QWEN 7B 1M	986K / 15.2 GB	4	6
COCO 7B Instruct 1M	986K / 15.2 GB	9	4
Apollo 7B	986K / 15.2 GB	8	0
Graph R1 7B	986K / 15.3 GB	7	3
Qwen2.5 7B Sky R1 Mini	986K / 15.2 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than YOYO-AI/Qwen2.5-7B-YOYO-super.