What are the hardware requirements for VisAlloc?

VisAlloc requires approximately 18.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed VisAlloc and how large is it?

VisAlloc is developed by pianzhikuang, a model with 9b 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 VisAlloc?

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

VisAlloc by pianzhikuang — VRAM 18.8GB

Name: VisAlloc
Author: pianzhikuang

VisAlloc is an open-source language model by pianzhikuang. Features: 9b LLM, VRAM: 18.8GB, License: apache-2.0, LLM Explorer Score: 0.28.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-9b Conversational Endpoints compatible Image-text-to-text Lookaway Qwen3 5 Region:us Safetensors Vision Vision-language Visual-question-answering

Model Card on HF 🤗: https://huggingface.co/pianzhikuang/VisAlloc

VisAlloc Parameters and Internals

LLM Name	VisAlloc
Repository 🤗	https://huggingface.co/pianzhikuang/VisAlloc
Base Model(s)	Qwen/Qwen3.5-9B Qwen/Qwen3.5-9B
Model Size	9b
Required VRAM	18.8 GB
Updated	2026-10-13
Maintainer	pianzhikuang
Model Type	qwen3_5
Model Files	18.8 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.5.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the VisAlloc 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 VisAlloc

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 Distilled 9B NPU2	256K / GB	3213	4
Clef Flash	0K / 18.8 GB	23285	791
Qwen3.5 9B	0K / 19.3 GB	12207758	1799
MiMo V2.6 Distill Qwen 9B	0K / 18.8 GB	5705	429
Qwable 9B Claude Fable 5	0K / 18.8 GB	1088	115
Ornith 1.0 9B	0K / 18.8 GB	897727	555
LensVLM 9B	0K / 18.8 GB	1840	258
Qwythos 9B Claude Mythos 5 1M	0K / 18.8 GB	37427	906
Negentropy Claude Opus 4.7 9B	0K / 18.8 GB	63	26
Qwen3.8 9B Distill	0K / 19.3 GB	5839	148

Note: green Score (e.g. "73.2") means that the model is better than pianzhikuang/VisAlloc.