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

Qwen3.5 4B Qwenputer requires approximately 18.8 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Qwen3.5 4B Qwenputer is developed by divagr1925, 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 Qwenputer?

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

Qwen3.5 4B Qwenputer by divagr1925 — VRAM 18.8GB, 256K context

Name: Qwen3.5 4B Qwenputer
Author: divagr1925

Qwen3.5 4B Qwenputer is an open-source language model by divagr1925. Features: 4b LLM, VRAM: 18.8GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.41.

Arithmetic Base model:merge:qwen/qwen3.5-... Base model:qwen/qwen3.5-4b Compiled-weights Conversational Doi:10.57967/hf/11140 Endpoints compatible Gated-deltanet Qwen3.5 Qwen3 5 text Qwenputer Region:us Risc-v Rv32im Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/divagr1925/Qwen3.5-4B-Qwenputer

Qwen3.5 4B Qwenputer Parameters and Internals

LLM Name	Qwen3.5 4B Qwenputer
Repository 🤗	https://huggingface.co/divagr1925/Qwen3.5-4B-Qwenputer
Base Model(s)	Qwen/Qwen3.5-4B Qwen/Qwen3.5-4B
Model Size	4b
Required VRAM	18.8 GB
Updated	2026-10-30
Maintainer	divagr1925
Model Type	qwen3_5_text
Model Files	3.8 GB: 1-of-8 2.2 GB: 2-of-8 2.2 GB: 3-of-8 2.2 GB: 4-of-8 2.2 GB: 5-of-8 2.1 GB: 6-of-8 2.2 GB: 7-of-8 1.9 GB: 8-of-8
Model Architecture	Qwen3_5ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	478656
Errors	replace

Rank the Qwen3.5 4B Qwenputer 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

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