What are the hardware requirements for Qwen3.5 2B Vi SFT?

Qwen3.5 2B Vi SFT requires approximately 4.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 2B Vi SFT and how large is it?

Qwen3.5 2B Vi SFT is developed by Phuc-HugigFace, a model with 2b 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 2B Vi SFT?

Qwen3.5 2B Vi SFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 2B Vi SFT by Phuc-HugigFace — VRAM 4.5GB

Name: Qwen3.5 2B Vi SFT
Author: Phuc-HugigFace

Qwen3.5 2B Vi SFT is an open-source language model by Phuc-HugigFace. Features: 2b LLM, VRAM: 4.5GB, License: apache-2.0.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-2b-bas... Conversational En Endpoints compatible Image-text-to-text Qwen3 5 Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/Phuc-HugigFace/Qwen3.5-2B-Vi-SFT

Qwen3.5 2B Vi SFT Parameters and Internals

LLM Name	Qwen3.5 2B Vi SFT
Repository 🤗	https://huggingface.co/Phuc-HugigFace/Qwen3.5-2B-Vi-SFT
Base Model(s)	Qwen/Qwen3.5-2B-Base Qwen/Qwen3.5-2B-Base
Model Size	2b
Required VRAM	4.5 GB
Updated	2026-09-13
Maintainer	Phuc-HugigFace
Model Type	qwen3_5
Model Files	4.5 GB: 1-of-1
Supported Languages	en
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|vision_pad\|>

Rank the Qwen3.5 2B Vi SFT 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 2B Vi SFT

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.5 2B	0K / 4.5 GB	2633311	352
WeMM Embedding 2B	0K / 5.4 GB	5433	68
Qwen3.5 2B Base	0K / 4.5 GB	809591	82
Qwen3.8 2B Distill	0K / 4.5 GB	2056	24
Qwen3.5 2B	0K / 4.5 GB	103487	18
Qwen3.5 2B Manumit V2	0K / 4.4 GB	431	0
Qwen3.8 2B	0K / 4.5 GB	319	13
JOSIE 2 2B OSS	0K / 4.5 GB	484	8
Qwen3.5 2B Finance Alpaca	0K / 4.4 GB	116	1
Qwen3.8 2B Heretic Max	0K / 4.4 GB	248	0

Note: green Score (e.g. "73.2") means that the model is better than Phuc-HugigFace/Qwen3.5-2B-Vi-SFT.