What are the hardware requirements for Qevacot 7B V2?

Qevacot 7B V2 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 Qevacot 7B V2 and how large is it?

Qevacot 7B V2 is developed by bunnycore, 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 Qevacot 7B V2?

Qevacot 7B V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qevacot 7B V2 by bunnycore — VRAM 15.2GB, 128K context

Name: Qevacot 7B V2
Author: bunnycore

Qevacot 7B V2 is an open-source language model by bunnycore. Features: 7b LLM, VRAM: 15.2GB, Context: 128K, Instruction-Based, Merged, LLM Explorer Score: 0.15.

Merged Model Arxiv:2306.01708 Base model:cran-may/t.e-8.1 Base model:eva-unit-01/eva-qwe... Base model:huihui-ai/qwen2.5-7... Base model:qwen/qwen2.5-7b Conversational Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/bunnycore/Qevacot-7B-v2

Qevacot 7B V2 Parameters and Internals

LLM Name	Qevacot 7B V2
Repository 🤗	https://huggingface.co/bunnycore/Qevacot-7B-v2
Base Model(s)	c10x/CoT-2.5 Qwen/Qwen2.5-7B EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1 huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2 Cran-May/T.E-8.1 c10x/CoT-2.5 Qwen/Qwen2.5-7B EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1 huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2 Cran-May/T.E-8.1
Merged Model	Yes
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-06-29
Maintainer	bunnycore
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
Model Architecture	Qwen2ForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qevacot 7B V2 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 Qevacot 7B V2

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 bunnycore/Qevacot-7B-v2.