What are the hardware requirements for Qwen3.5FundusReasoner Base?

Qwen3.5FundusReasoner Base requires approximately 18.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5FundusReasoner Base and how large is it?

Qwen3.5FundusReasoner Base is developed by zym1105, a model with 9.4b 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 Qwen3.5FundusReasoner Base?

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

Qwen3.5FundusReasoner Base by zym1105 — VRAM 18.8GB

Name: Qwen3.5FundusReasoner Base
Author: zym1105

Qwen3.5FundusReasoner Base is an open-source language model by zym1105. Features: 9.4b LLM, VRAM: 18.8GB, License: other, LLM Explorer Score: 0.27.

Conversational En Endpoints compatible Fundus Image-text-to-text Interpretable-ai Medical-ai Multimodal Ophthalmology Qwen Qwen3 5 Region:us Safetensors Vision Vision-language Visual-grounding Zh

Model Card on HF 🤗: https://huggingface.co/zym1105/Qwen3.5FundusReasoner_base

Qwen3.5FundusReasoner Base Parameters and Internals

LLM Name	Qwen3.5FundusReasoner Base
Repository 🤗	https://huggingface.co/zym1105/Qwen3.5FundusReasoner_base
Model Size	9.4b
Required VRAM	18.8 GB
Updated	2026-09-04
Maintainer	zym1105
Model Type	qwen3_5
Model Files	18.8 GB 0.0 GB
Supported Languages	zh en
Model Architecture	Qwen3_5ForConditionalGeneration
License	other
Model Max Length	262144
Transformers Version	5.6.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

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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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