What are the hardware requirements for Qwen3.5 4B VerIH Step636?

Qwen3.5 4B VerIH Step636 requires approximately 18.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 4B VerIH Step636 and how large is it?

Qwen3.5 4B VerIH Step636 is developed by ConnorYU, a model with 4b 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 Qwen3.5 4B VerIH Step636?

Qwen3.5 4B VerIH Step636 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 4B VerIH Step636 by ConnorYU — VRAM 18.2GB

Name: Qwen3.5 4B VerIH Step636
Author: ConnorYU

Qwen3.5 4B VerIH Step636 is an open-source language model by ConnorYU. Features: 4b LLM, VRAM: 18.2GB, LLM Explorer Score: 0.27.

Qwen3 5 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/ConnorYU/Qwen3.5-4B-VerIH-step636

Qwen3.5 4B VerIH Step636 Parameters and Internals

LLM Name	Qwen3.5 4B VerIH Step636
Repository 🤗	https://huggingface.co/ConnorYU/Qwen3.5-4B-VerIH-step636
Model Size	4b
Required VRAM	18.2 GB
Updated	2026-08-22
Maintainer	ConnorYU
Model Type	qwen3_5
Model Files	18.2 GB
Model Architecture	Qwen3_5ForConditionalGeneration
Model Max Length	262144
Transformers Version	5.10.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.5 4B VerIH Step636 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 Qwen3.5 4B VerIH Step636

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.5 4B	0K / 9.3 GB	6575502	801
Agents A1 4B	0K / 9.1 GB	177578	72
NuExtract3	0K / 0.2 GB	441570	324
Qwen3.8 4B Distill	0K / 9.3 GB	1878	26
Fara1.5 4B	0K / 9.1 GB	4934	39
Qwen3.5 4B Base	0K / 9.3 GB	227814	79
AREX Turbo	0K / 9.1 GB	1350	44
DeepSeek V4 Pro Qwen3.5 4B	0K / 9.3 GB	3476	9
Qwen3.5 4B	0K / 9.3 GB	139961	26
Mephisto 4B 0725	0K / 8.6 GB	3280	6

Note: green Score (e.g. "73.2") means that the model is better than ConnorYU/Qwen3.5-4B-VerIH-step636.