What are the hardware requirements for EVA Norns Qwen2.5 V0.1?

EVA Norns Qwen2.5 V0.1 requires approximately 16.2 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 EVA Norns Qwen2.5 V0.1 and how large is it?

EVA Norns Qwen2.5 V0.1 is developed by win10, 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 EVA Norns Qwen2.5 V0.1?

EVA Norns Qwen2.5 V0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EVA Norns Qwen2.5 V0.1 by win10 — VRAM 16.2GB, 128K context

Name: EVA Norns Qwen2.5 V0.1
Author: win10

EVA Norns Qwen2.5 V0.1 is an open-source language model by win10. Features: 7b LLM, VRAM: 16.2GB, Context: 128K, Merged, LLM Explorer Score: 0.23.

Merged Model Arxiv:2306.01708 Base model:eva-unit-01/eva-qwe... Base model:win10/urdandi-qwen2... Conversational Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/win10/EVA-Norns-Qwen2.5-v0.1

EVA Norns Qwen2.5 V0.1 Parameters and Internals

LLM Name	EVA Norns Qwen2.5 V0.1
Repository 🤗	https://huggingface.co/win10/EVA-Norns-Qwen2.5-v0.1
Base Model(s)	EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1 win10/Urdandi-Qwen2.5-7B EVA-UNIT-01/EVA-Qwen2.5-7B-v0.1 win10/Urdandi-Qwen2.5-7B
Merged Model	Yes
Model Size	7b
Required VRAM	16.2 GB
Updated	2026-08-04
Maintainer	win10
Model Type	qwen2
Model Files	1.1 GB: 1-of-30 1.1 GB: 2-of-30 0.5 GB: 3-of-30 0.5 GB: 4-of-30 0.5 GB: 5-of-30 0.5 GB: 6-of-30 0.5 GB: 7-of-30 0.5 GB: 8-of-30 0.5 GB: 9-of-30 0.5 GB: 10-of-30 0.5 GB: 11-of-30 0.5 GB: 12-of-30 0.5 GB: 13-of-30 0.5 GB: 14-of-30 0.5 GB: 15-of-30 0.5 GB: 16-of-30 0.5 GB: 17-of-30 0.5 GB: 18-of-30 0.5 GB: 19-of-30 0.5 GB: 20-of-30 0.5 GB: 21-of-30 0.5 GB: 22-of-30 0.5 GB: 23-of-30 0.5 GB: 24-of-30 0.5 GB: 25-of-30 0.5 GB: 26-of-30 0.5 GB: 27-of-30 0.5 GB: 28-of-30 0.5 GB: 29-of-30 0.5 GB: 30-of-30
Model Architecture	Qwen2ForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.45.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the EVA Norns Qwen2.5 V0.1 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 EVA Norns Qwen2.5 V0.1

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Preview	986K / 15.2 GB	10	0
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Hush Qwen2.5 7B V1.2	986K / 15.2 GB	4	1
Hush Qwen2.5 7B V1.1	986K / 15.2 GB	5	1
Hush Qwen2.5 7B V1.4	986K / 15.2 GB	8	1
Hush Qwen2.5 7B Preview	986K / 15.2 GB	5	0
Hush Qwen2.5 7B V1.3	986K / 15.2 GB	10	2
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen 2.5 7B Exp Sce	986K / 15.2 GB	10	2
Qwen2.5 7B MixStock V0.1	986K / 15.2 GB	6	3

Note: green Score (e.g. "73.2") means that the model is better than win10/EVA-Norns-Qwen2.5-v0.1.